Spaces:
Runtime error
Runtime error
Add grabo dataset to app
Browse files- app.py +33 -2
- audio_grabo.wav +0 -0
- audio_snips.wav +0 -0
- espnet-slu-snips/.DS_Store +0 -0
- espnet-slu-snips/.gitattributes +27 -0
- espnet-slu-snips/README.md +13 -0
- espnet-slu-snips/config.yaml +295 -0
- espnet-slu-snips/valid.acc.ave_10best.pth +3 -0
- grabo/config.yaml +228 -0
- grabo/feats_stats.npz +0 -0
- grabo/valid.acc.ave_10best.pth +3 -0
app.py
CHANGED
@@ -8,6 +8,12 @@ from espnet2.utils.types import str_or_none
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from espnet2.bin.asr_inference import Speech2Text
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from subprocess import call
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import os
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with open('s3prl.sh', 'rb') as file:
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script = file.read()
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@@ -35,6 +41,13 @@ speech2text_fsc = Speech2Text.from_pretrained(
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nbest=1
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)
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speech2text_catslu = Speech2Text.from_pretrained(
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asr_train_config="catslu/config.yaml",
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asr_model_file="catslu/valid.acc.ave_5best.pth",
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@@ -42,6 +55,14 @@ speech2text_catslu = Speech2Text.from_pretrained(
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nbest=1
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)
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def inference(wav,data):
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with torch.no_grad():
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if data == "english_slurp":
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@@ -78,6 +99,16 @@ def inference(wav,data):
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nbests = speech2text_catslu(speech)
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text, *_ = nbests[0]
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text=text.split(" ")[0]
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# intent=text.split(" ")[0]
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# action=intent.split("_")[0]
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# objects=intent.split("_")[1]
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@@ -96,12 +127,12 @@ title = "ESPnet2-SLU"
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description = "Gradio demo for ESPnet2-SLU: Advancing Spoken Language Understanding through ESPnet. To use it, simply record your audio or click one of the examples to load them. Read more at the links below."
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article = "<p style='text-align: center'><a href='https://github.com/espnet/espnet' target='_blank'>Github Repo</a></p>"
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-
examples=[['audio_slurp.flac',"english_slurp"],['audio_fsc.wav',"english_fsc"],['audio_catslu.wav',"chinese"]]
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# gr.inputs.Textbox(label="input text",lines=10),gr.inputs.Radio(choices=["english"], type="value", default="english", label="language")
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gr.Interface(
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inference,
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-
[gr.inputs.Audio(label="input audio",source = "microphone", type="file"),gr.inputs.Radio(choices=["english_slurp","english_fsc","chinese"], type="value", default="english_slurp", label="Dataset")],
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gr.outputs.Textbox(type="str", label="Output"),
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title=title,
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description=description,
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from espnet2.bin.asr_inference import Speech2Text
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from subprocess import call
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import os
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from espnet_model_zoo.downloader import ModelDownloader
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d = ModelDownloader()
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tag="ftshijt/open_li52_asr_train_asr_raw_bpe7000_valid.acc.ave_10best"
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a1= (d.download_and_unpack(tag))
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# print(a1)
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# exit()
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with open('s3prl.sh', 'rb') as file:
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script = file.read()
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nbest=1
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)
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speech2text_snips = Speech2Text.from_pretrained(
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asr_train_config="espnet-slu-snips/config.yaml",
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asr_model_file="espnet-slu-snips/valid.acc.ave_10best.pth",
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# Decoding parameters are not included in the model file
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nbest=1
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)
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speech2text_catslu = Speech2Text.from_pretrained(
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asr_train_config="catslu/config.yaml",
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asr_model_file="catslu/valid.acc.ave_5best.pth",
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nbest=1
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)
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speech2text_grabo = Speech2Text.from_pretrained(
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asr_train_config="grabo/config.yaml",
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asr_model_file="grabo/valid.acc.ave_10best.pth",
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ctc_weight=0.0,
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# Decoding parameters are not included in the model file
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nbest=1
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)
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def inference(wav,data):
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with torch.no_grad():
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if data == "english_slurp":
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nbests = speech2text_catslu(speech)
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text, *_ = nbests[0]
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text=text.split(" ")[0]
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# elif data == "english_snips":
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# print(wav.name)
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# speech, rate = soundfile.read(wav.name)
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# nbests = speech2text_snips(speech)
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# text, *_ = nbests[0]
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elif data == "dutch":
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print(wav.name)
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speech, rate = soundfile.read(wav.name)
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nbests = speech2text_grabo(speech)
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text, *_ = nbests[0]
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# intent=text.split(" ")[0]
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# action=intent.split("_")[0]
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# objects=intent.split("_")[1]
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description = "Gradio demo for ESPnet2-SLU: Advancing Spoken Language Understanding through ESPnet. To use it, simply record your audio or click one of the examples to load them. Read more at the links below."
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article = "<p style='text-align: center'><a href='https://github.com/espnet/espnet' target='_blank'>Github Repo</a></p>"
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examples=[['audio_slurp.flac',"english_slurp"],['audio_fsc.wav',"english_fsc"],['audio_grabo.wav',"dutch"],['audio_catslu.wav',"chinese"]]
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# gr.inputs.Textbox(label="input text",lines=10),gr.inputs.Radio(choices=["english"], type="value", default="english", label="language")
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gr.Interface(
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inference,
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[gr.inputs.Audio(label="input audio",source = "microphone", type="file"),gr.inputs.Radio(choices=["english_slurp","english_fsc","dutch","chinese"], type="value", default="english_slurp", label="Dataset")],
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gr.outputs.Textbox(type="str", label="Output"),
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title=title,
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description=description,
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audio_grabo.wav
ADDED
Binary file (392 kB). View file
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audio_snips.wav
ADDED
Binary file (112 kB). View file
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espnet-slu-snips/.DS_Store
ADDED
Binary file (6.15 kB). View file
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espnet-slu-snips/.gitattributes
ADDED
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*.7z filter=lfs diff=lfs merge=lfs -text
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*.arrow filter=lfs diff=lfs merge=lfs -text
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*.bin filter=lfs diff=lfs merge=lfs -text
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*.bin.* filter=lfs diff=lfs merge=lfs -text
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*.bz2 filter=lfs diff=lfs merge=lfs -text
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*.ftz filter=lfs diff=lfs merge=lfs -text
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*.gz filter=lfs diff=lfs merge=lfs -text
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*.h5 filter=lfs diff=lfs merge=lfs -text
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*.joblib filter=lfs diff=lfs merge=lfs -text
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*.lfs.* filter=lfs diff=lfs merge=lfs -text
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*.model filter=lfs diff=lfs merge=lfs -text
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*.msgpack filter=lfs diff=lfs merge=lfs -text
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*.onnx filter=lfs diff=lfs merge=lfs -text
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*.ot filter=lfs diff=lfs merge=lfs -text
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*.parquet filter=lfs diff=lfs merge=lfs -text
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*.pb filter=lfs diff=lfs merge=lfs -text
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*.pt filter=lfs diff=lfs merge=lfs -text
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*.pth filter=lfs diff=lfs merge=lfs -text
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*.rar filter=lfs diff=lfs merge=lfs -text
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saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.tar.* filter=lfs diff=lfs merge=lfs -text
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*.tflite filter=lfs diff=lfs merge=lfs -text
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*.tgz filter=lfs diff=lfs merge=lfs -text
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*.xz filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zstandard filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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espnet-slu-snips/README.md
ADDED
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Fine-tune snips dataset for SLU task using pretrained ASR model with hubert feature
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---
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language:
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- en
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receipe: "https://github.com/espnet/espnet/tree/master/egs2/snips/asr1"
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datasets:
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- snips: smart-lights-en-close-field
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metrics:
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- F1 score: 91.7
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---
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espnet-slu-snips/config.yaml
ADDED
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config: conf/tuning/train_asr_hubert_conformer.yaml
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print_config: false
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log_level: INFO
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dry_run: false
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iterator_type: sequence
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output_dir: exp/asr_train_asr_hubert_conformer_raw_bpe100_init_paramexpexp_hubert_large_ll60k_weighted_perturbasr_train_asr_conformer7_hubert_960hr_large_raw_en_bpe5000_sp26epoch.pth:::decoder.output_layer,decoder.embed.0,ctc.ctc_lo_sp
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ngpu: 1
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seed: 0
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num_workers: 1
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num_att_plot: 3
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dist_backend: nccl
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dist_init_method: env://
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dist_world_size: null
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dist_rank: null
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local_rank: null
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dist_master_addr: null
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dist_master_port: null
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dist_launcher: null
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multiprocessing_distributed: false
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unused_parameters: false
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sharded_ddp: false
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cudnn_enabled: true
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cudnn_benchmark: false
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cudnn_deterministic: true
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collect_stats: false
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write_collected_feats: false
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max_epoch: 500
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patience: null
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val_scheduler_criterion:
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- valid
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- loss
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early_stopping_criterion:
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- valid
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- loss
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- min
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best_model_criterion:
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- - valid
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- acc
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- max
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+
keep_nbest_models: 10
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+
grad_clip: 5.0
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+
grad_clip_type: 2.0
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+
grad_noise: false
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+
accum_grad: 1
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+
no_forward_run: false
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+
resume: true
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+
train_dtype: float32
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+
use_amp: false
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+
log_interval: null
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use_tensorboard: true
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use_wandb: false
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wandb_project: null
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+
wandb_id: null
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wandb_entity: null
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wandb_name: null
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+
wandb_model_log_interval: -1
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detect_anomaly: false
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pretrain_path: null
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+
init_param:
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+
- exp/exp_hubert_large_ll60k_weighted_perturb/asr_train_asr_conformer7_hubert_960hr_large_raw_en_bpe5000_sp/26epoch.pth:::decoder.output_layer,decoder.embed.0,ctc.ctc_lo
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+
ignore_init_mismatch: false
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+
freeze_param:
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+
- frontend.upstream
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+
num_iters_per_epoch: null
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+
batch_size: 20
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+
valid_batch_size: null
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+
batch_bins: 1000000
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+
valid_batch_bins: null
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+
train_shape_file:
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+
- exp/asr_stats_raw_bpe100_sp/train/speech_shape
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+
- exp/asr_stats_raw_bpe100_sp/train/text_shape.bpe
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+
valid_shape_file:
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- exp/asr_stats_raw_bpe100_sp/valid/speech_shape
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+
- exp/asr_stats_raw_bpe100_sp/valid/text_shape.bpe
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+
batch_type: folded
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76 |
+
valid_batch_type: null
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+
fold_length:
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- 80000
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- 150
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sort_in_batch: descending
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81 |
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sort_batch: descending
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+
multiple_iterator: false
|
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+
chunk_length: 500
|
84 |
+
chunk_shift_ratio: 0.5
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+
num_cache_chunks: 1024
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+
train_data_path_and_name_and_type:
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87 |
+
- - dump/raw/train_sp/wav.scp
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88 |
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- speech
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89 |
+
- sound
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90 |
+
- - dump/raw/train_sp/text
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91 |
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- text
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92 |
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- text
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valid_data_path_and_name_and_type:
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94 |
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- - dump/raw/dev/wav.scp
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95 |
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- speech
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96 |
+
- sound
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97 |
+
- - dump/raw/dev/text
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- text
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+
- text
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100 |
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102 |
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104 |
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105 |
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optim_conf:
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106 |
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lr: 0.0002
|
107 |
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scheduler: warmuplr
|
108 |
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scheduler_conf:
|
109 |
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warmup_steps: 2000
|
110 |
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token_list:
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111 |
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112 |
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113 |
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173 |
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176 |
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177 |
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178 |
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179 |
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190 |
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191 |
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192 |
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193 |
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194 |
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195 |
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|
196 |
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197 |
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198 |
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199 |
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200 |
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201 |
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202 |
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203 |
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204 |
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205 |
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206 |
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207 |
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208 |
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209 |
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210 |
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|
211 |
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|
212 |
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input_size: null
|
213 |
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ctc_conf:
|
214 |
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dropout_rate: 0.0
|
215 |
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ctc_type: builtin
|
216 |
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reduce: true
|
217 |
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ignore_nan_grad: true
|
218 |
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model_conf:
|
219 |
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ctc_weight: 0.3
|
220 |
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lsm_weight: 0.1
|
221 |
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length_normalized_loss: false
|
222 |
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extract_feats_in_collect_stats: false
|
223 |
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use_preprocessor: true
|
224 |
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token_type: bpe
|
225 |
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bpemodel: data/token_list/bpe_unigram100/bpe.model
|
226 |
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non_linguistic_symbols: null
|
227 |
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cleaner: null
|
228 |
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g2p: null
|
229 |
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speech_volume_normalize: null
|
230 |
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rir_scp: null
|
231 |
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rir_apply_prob: 1.0
|
232 |
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noise_scp: null
|
233 |
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noise_apply_prob: 1.0
|
234 |
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noise_db_range: '13_15'
|
235 |
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frontend: s3prl
|
236 |
+
frontend_conf:
|
237 |
+
frontend_conf:
|
238 |
+
upstream: hubert_large_ll60k
|
239 |
+
download_dir: ./hub
|
240 |
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multilayer_feature: true
|
241 |
+
fs: 16k
|
242 |
+
specaug: specaug
|
243 |
+
specaug_conf:
|
244 |
+
apply_time_warp: true
|
245 |
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time_warp_window: 5
|
246 |
+
time_warp_mode: bicubic
|
247 |
+
apply_freq_mask: true
|
248 |
+
freq_mask_width_range:
|
249 |
+
- 0
|
250 |
+
- 30
|
251 |
+
num_freq_mask: 2
|
252 |
+
apply_time_mask: true
|
253 |
+
time_mask_width_range:
|
254 |
+
- 0
|
255 |
+
- 40
|
256 |
+
num_time_mask: 2
|
257 |
+
normalize: utterance_mvn
|
258 |
+
normalize_conf: {}
|
259 |
+
preencoder: linear
|
260 |
+
preencoder_conf:
|
261 |
+
input_size: 1024
|
262 |
+
output_size: 80
|
263 |
+
encoder: conformer
|
264 |
+
encoder_conf:
|
265 |
+
output_size: 512
|
266 |
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attention_heads: 8
|
267 |
+
linear_units: 2048
|
268 |
+
num_blocks: 12
|
269 |
+
dropout_rate: 0.1
|
270 |
+
positional_dropout_rate: 0.1
|
271 |
+
attention_dropout_rate: 0.1
|
272 |
+
input_layer: conv2d
|
273 |
+
normalize_before: true
|
274 |
+
macaron_style: true
|
275 |
+
pos_enc_layer_type: rel_pos
|
276 |
+
selfattention_layer_type: rel_selfattn
|
277 |
+
activation_type: swish
|
278 |
+
use_cnn_module: true
|
279 |
+
cnn_module_kernel: 31
|
280 |
+
postencoder: null
|
281 |
+
postencoder_conf: {}
|
282 |
+
decoder: transformer
|
283 |
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decoder_conf:
|
284 |
+
attention_heads: 8
|
285 |
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linear_units: 2048
|
286 |
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num_blocks: 6
|
287 |
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dropout_rate: 0.1
|
288 |
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positional_dropout_rate: 0.1
|
289 |
+
self_attention_dropout_rate: 0.1
|
290 |
+
src_attention_dropout_rate: 0.1
|
291 |
+
required:
|
292 |
+
- output_dir
|
293 |
+
- token_list
|
294 |
+
version: 0.10.3a3
|
295 |
+
distributed: false
|
espnet-slu-snips/valid.acc.ave_10best.pth
ADDED
@@ -0,0 +1,3 @@
|
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|
|
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|
|
1 |
+
version https://git-lfs.github.com/spec/v1
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oid sha256:a6976d53b33b25193e7d3a97cf9766d9ad41b1648b7ad0d807154c70ff23a33e
|
3 |
+
size 1701692895
|
grabo/config.yaml
ADDED
@@ -0,0 +1,228 @@
|
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|
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|
|
|
|
|
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|
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|
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|
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|
|
|
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|
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|
|
|
|
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|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
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|
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|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
config: conf/train_asr.yaml
|
2 |
+
print_config: false
|
3 |
+
log_level: INFO
|
4 |
+
dry_run: false
|
5 |
+
iterator_type: sequence
|
6 |
+
output_dir: exp/asr_conformer_mono16k_warmup800_lr2e-4_accum2
|
7 |
+
ngpu: 1
|
8 |
+
seed: 0
|
9 |
+
num_workers: 1
|
10 |
+
num_att_plot: 3
|
11 |
+
dist_backend: nccl
|
12 |
+
dist_init_method: env://
|
13 |
+
dist_world_size: null
|
14 |
+
dist_rank: null
|
15 |
+
local_rank: 0
|
16 |
+
dist_master_addr: null
|
17 |
+
dist_master_port: null
|
18 |
+
dist_launcher: null
|
19 |
+
multiprocessing_distributed: false
|
20 |
+
unused_parameters: false
|
21 |
+
sharded_ddp: false
|
22 |
+
cudnn_enabled: true
|
23 |
+
cudnn_benchmark: false
|
24 |
+
cudnn_deterministic: true
|
25 |
+
collect_stats: false
|
26 |
+
write_collected_feats: false
|
27 |
+
max_epoch: 250
|
28 |
+
patience: null
|
29 |
+
val_scheduler_criterion:
|
30 |
+
- valid
|
31 |
+
- loss
|
32 |
+
early_stopping_criterion:
|
33 |
+
- valid
|
34 |
+
- loss
|
35 |
+
- min
|
36 |
+
best_model_criterion:
|
37 |
+
- - valid
|
38 |
+
- acc
|
39 |
+
- max
|
40 |
+
keep_nbest_models: 10
|
41 |
+
nbest_averaging_interval: 0
|
42 |
+
grad_clip: 5.0
|
43 |
+
grad_clip_type: 2.0
|
44 |
+
grad_noise: false
|
45 |
+
accum_grad: 2
|
46 |
+
no_forward_run: false
|
47 |
+
resume: true
|
48 |
+
train_dtype: float32
|
49 |
+
use_amp: false
|
50 |
+
log_interval: null
|
51 |
+
use_tensorboard: true
|
52 |
+
use_wandb: false
|
53 |
+
wandb_project: null
|
54 |
+
wandb_id: null
|
55 |
+
wandb_entity: null
|
56 |
+
wandb_name: null
|
57 |
+
wandb_model_log_interval: -1
|
58 |
+
detect_anomaly: false
|
59 |
+
pretrain_path: null
|
60 |
+
init_param: []
|
61 |
+
ignore_init_mismatch: false
|
62 |
+
freeze_param: []
|
63 |
+
num_iters_per_epoch: null
|
64 |
+
batch_size: 20
|
65 |
+
valid_batch_size: null
|
66 |
+
batch_bins: 2000000
|
67 |
+
valid_batch_bins: null
|
68 |
+
train_shape_file:
|
69 |
+
- exp/asr_stats_raw_word_sp/train/speech_shape
|
70 |
+
- exp/asr_stats_raw_word_sp/train/text_shape.word
|
71 |
+
valid_shape_file:
|
72 |
+
- exp/asr_stats_raw_word_sp/valid/speech_shape
|
73 |
+
- exp/asr_stats_raw_word_sp/valid/text_shape.word
|
74 |
+
batch_type: numel
|
75 |
+
valid_batch_type: null
|
76 |
+
fold_length:
|
77 |
+
- 80000
|
78 |
+
- 150
|
79 |
+
sort_in_batch: descending
|
80 |
+
sort_batch: descending
|
81 |
+
multiple_iterator: false
|
82 |
+
chunk_length: 500
|
83 |
+
chunk_shift_ratio: 0.5
|
84 |
+
num_cache_chunks: 1024
|
85 |
+
train_data_path_and_name_and_type:
|
86 |
+
- - dump/raw/train_sp/wav.scp
|
87 |
+
- speech
|
88 |
+
- sound
|
89 |
+
- - dump/raw/train_sp/text
|
90 |
+
- text
|
91 |
+
- text
|
92 |
+
valid_data_path_and_name_and_type:
|
93 |
+
- - dump/raw/dev/wav.scp
|
94 |
+
- speech
|
95 |
+
- sound
|
96 |
+
- - dump/raw/dev/text
|
97 |
+
- text
|
98 |
+
- text
|
99 |
+
allow_variable_data_keys: false
|
100 |
+
max_cache_size: 0.0
|
101 |
+
max_cache_fd: 32
|
102 |
+
valid_max_cache_size: null
|
103 |
+
optim: adam
|
104 |
+
optim_conf:
|
105 |
+
lr: 0.0002
|
106 |
+
scheduler: warmuplr
|
107 |
+
scheduler_conf:
|
108 |
+
warmup_steps: 800
|
109 |
+
token_list:
|
110 |
+
- <blank>
|
111 |
+
- <unk>
|
112 |
+
- <move_rel-throttle="slow"-distance="little"-direction="backward"-/>
|
113 |
+
- <move_rel-throttle="slow"-distance="normal"-direction="backward"-/>
|
114 |
+
- <move_rel-throttle="slow"-distance="alot"-direction="backward"-/>
|
115 |
+
- <move_abs-throttle="fast"-pos_x="centerx"-pos_y="centery"-/>
|
116 |
+
- <move_abs-throttle="fast"-pos_x="left"-pos_y="up"-/>
|
117 |
+
- <move_abs-throttle="fast"-pos_x="right"-pos_y="down"-/>
|
118 |
+
- <move_abs-throttle="slow"-pos_x="centerx"-pos_y="centery"-/>
|
119 |
+
- <move_abs-throttle="slow"-pos_x="left"-pos_y="up"-/>
|
120 |
+
- <move_abs-throttle="slow"-pos_x="right"-pos_y="down"-/>
|
121 |
+
- <turn_rel-throttle="slow"-angle="south"-/>
|
122 |
+
- <move_rel-throttle="fast"-distance="little"-direction="forward"-/>
|
123 |
+
- <turn_rel-throttle="slow"-angle="east"-/>
|
124 |
+
- <turn_rel-throttle="slow"-angle="west"-/>
|
125 |
+
- <turn_rel-throttle="fast"-angle="south"-/>
|
126 |
+
- <turn_rel-throttle="fast"-angle="east"-/>
|
127 |
+
- <turn_rel-throttle="fast"-angle="west"-/>
|
128 |
+
- <turn_abs-angle="west"-/>
|
129 |
+
- <turn_abs-angle="east"-/>
|
130 |
+
- <turn_abs-angle="north"-/>
|
131 |
+
- <turn_abs-angle="south"-/>
|
132 |
+
- <lift-position="up"-/>
|
133 |
+
- <move_rel-throttle="fast"-distance="normal"-direction="forward"-/>
|
134 |
+
- <lift-position="down"-/>
|
135 |
+
- <approach-throttle="fast"-/>
|
136 |
+
- <approach-throttle="slow"-/>
|
137 |
+
- <grab-grabber="close"-/>
|
138 |
+
- <grab-grabber="open"-/>
|
139 |
+
- <pointer-state="off"-/>
|
140 |
+
- <pointer-state="on"-/>
|
141 |
+
- <move_rel-throttle="fast"-distance="alot"-direction="forward"-/>
|
142 |
+
- <move_rel-throttle="slow"-distance="little"-direction="forward"-/>
|
143 |
+
- <move_rel-throttle="slow"-distance="normal"-direction="forward"-/>
|
144 |
+
- <move_rel-throttle="slow"-distance="alot"-direction="forward"-/>
|
145 |
+
- <move_rel-throttle="fast"-distance="little"-direction="backward"-/>
|
146 |
+
- <move_rel-throttle="fast"-distance="normal"-direction="backward"-/>
|
147 |
+
- <move_rel-throttle="fast"-distance="alot"-direction="backward"-/>
|
148 |
+
- <sos/eos>
|
149 |
+
init: null
|
150 |
+
input_size: null
|
151 |
+
ctc_conf:
|
152 |
+
dropout_rate: 0.0
|
153 |
+
ctc_type: builtin
|
154 |
+
reduce: true
|
155 |
+
ignore_nan_grad: true
|
156 |
+
model_conf:
|
157 |
+
ctc_weight: 0.0
|
158 |
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lsm_weight: 0.0
|
159 |
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length_normalized_loss: false
|
160 |
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use_preprocessor: true
|
161 |
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token_type: word
|
162 |
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bpemodel: null
|
163 |
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non_linguistic_symbols: null
|
164 |
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cleaner: null
|
165 |
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g2p: null
|
166 |
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speech_volume_normalize: null
|
167 |
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rir_scp: null
|
168 |
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rir_apply_prob: 1.0
|
169 |
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noise_scp: null
|
170 |
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noise_apply_prob: 1.0
|
171 |
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noise_db_range: '13_15'
|
172 |
+
frontend: default
|
173 |
+
frontend_conf:
|
174 |
+
fs: 16000
|
175 |
+
specaug: specaug
|
176 |
+
specaug_conf:
|
177 |
+
apply_time_warp: true
|
178 |
+
time_warp_window: 5
|
179 |
+
time_warp_mode: bicubic
|
180 |
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apply_freq_mask: true
|
181 |
+
freq_mask_width_range:
|
182 |
+
- 0
|
183 |
+
- 30
|
184 |
+
num_freq_mask: 2
|
185 |
+
apply_time_mask: true
|
186 |
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time_mask_width_range:
|
187 |
+
- 0
|
188 |
+
- 40
|
189 |
+
num_time_mask: 2
|
190 |
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normalize: global_mvn
|
191 |
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normalize_conf:
|
192 |
+
stats_file: grabo/feats_stats.npz
|
193 |
+
preencoder: null
|
194 |
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preencoder_conf: {}
|
195 |
+
encoder: conformer
|
196 |
+
encoder_conf:
|
197 |
+
output_size: 256
|
198 |
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attention_heads: 4
|
199 |
+
linear_units: 2048
|
200 |
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num_blocks: 12
|
201 |
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dropout_rate: 0.1
|
202 |
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positional_dropout_rate: 0.1
|
203 |
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attention_dropout_rate: 0.0
|
204 |
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input_layer: conv2d
|
205 |
+
normalize_before: true
|
206 |
+
macaron_style: true
|
207 |
+
rel_pos_type: legacy
|
208 |
+
pos_enc_layer_type: rel_pos
|
209 |
+
selfattention_layer_type: rel_selfattn
|
210 |
+
activation_type: swish
|
211 |
+
use_cnn_module: true
|
212 |
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cnn_module_kernel: 15
|
213 |
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postencoder: null
|
214 |
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postencoder_conf: {}
|
215 |
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decoder: transformer
|
216 |
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decoder_conf:
|
217 |
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attention_heads: 4
|
218 |
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linear_units: 2048
|
219 |
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num_blocks: 6
|
220 |
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dropout_rate: 0.1
|
221 |
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positional_dropout_rate: 0.1
|
222 |
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self_attention_dropout_rate: 0.0
|
223 |
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src_attention_dropout_rate: 0.0
|
224 |
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required:
|
225 |
+
- output_dir
|
226 |
+
- token_list
|
227 |
+
version: 0.10.5a1
|
228 |
+
distributed: false
|
grabo/feats_stats.npz
ADDED
Binary file (1.4 kB). View file
|
|
grabo/valid.acc.ave_10best.pth
ADDED
@@ -0,0 +1,3 @@
|
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|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
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2 |
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oid sha256:94487c8e126609d0c78cf97de505ba83e671b4c3bc2285c6a1b02e131a4af7b9
|
3 |
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size 172176105
|