Text2Text Generation
speechbrain
English
G2P
Grapheme-to-Phoneme
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+ ---
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+ license: apache-2.0
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+ language: "en"
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+ thumbnail:
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+ tags:
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+ - G2P
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+ - Grapheme-to-Phoneme
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+ - speechbrain
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+ - text2text-generation
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+ datasets:
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+ - Librispeech
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+ metrics:
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+ - Phone-Error-Rate
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+ widget:
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+ - text: "English is tough. It can be understood through thorough thought though."
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+ ---
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+ # SoundChoice: Grapheme-to-Phoneme Models with Semantic Disambiguation
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+
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+ This repository provides all the necessary tools to perform English grapheme-to-phoneme conversion with a pretrained SoundChoice G2P model using SpeechBrain. It is trained on LibriG2P training data derived from [LibriSpeech Alignments](https://zenodo.org/record/2619474#.YuCdaC8r1ZF) and [Google Wikipedia](https://github.com/google/WikipediaHomographData)
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+
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+
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+ ## Install SpeechBrain
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+
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+ First of all, please install SpeechBrain with the following command (local installation):
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+
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+ ```bash
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+ pip install speechbrain
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+ pip install transformers
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+ ```
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+
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+ Please notice that we encourage you to read our tutorials and learn more about
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+ [SpeechBrain](https://speechbrain.github.io).
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+
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+ ## Perform G2P Conversion
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+
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+ Please follow the example below to perform grapheme-to-phoneme conversion with a high-level wrapper.
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+
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+ ```python
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+ from speechbrain.pretrained import GraphemeToPhoneme
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+ g2p = GraphemeToPhoneme.from_hparams("speechbrain/soundchoice-g2p")
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+ text = "To be or not to be, that is the question"
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+ phonemes = g2p(text)
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+ ```
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+
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+ Given below is the expected output
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+ ```python
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+ >>> phonemes
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+ ['T', 'UW', ' ', 'B', 'IY', ' ', 'AO', 'R', ' ', 'N', 'AA', 'T', ' ', 'T', 'UW', ' ', 'B', 'IY', ' ', 'DH', 'AE', 'T', ' ', 'IH', 'Z', ' ', 'DH', 'AH', ' ', 'K', 'W', 'EH', 'S', 'CH', 'AH', 'N']
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+ ```
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+
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+ To perform G2P conversion on a batch of text, pass
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+ an array of strings to the interface:
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+
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+ ```python
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+ items = [
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+ "All's Well That Ends Well",
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+ "The Merchant of Venice",
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+ "The Two Gentlemen of Verona",
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+ "The Comedy of Errors"
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+ ]
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+ transcriptions = g2p(items)
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+ ```
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+
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+ Given below is the expected output:
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+
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+ ```python
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+ >>> transcriptions
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+ [['AO', 'L', 'Z', ' ', 'W', 'EH', 'L', ' ', 'DH', 'AE', 'T', ' ', 'EH', 'N', 'D', 'Z', ' ', 'W', 'EH', 'L'], ['DH', 'AH', ' ', 'M', 'ER', 'CH', 'AH', 'N', 'T', ' ', 'AH', 'V', ' ', 'V', 'EH', 'N', 'AH', 'S'], ['DH', 'AH', ' ', 'T', 'UW', ' ', 'JH', 'EH', 'N', 'T', 'AH', 'L', 'M', 'IH', 'N', ' ', 'AH', 'V', ' ', 'V', 'ER', 'OW', 'N', 'AH'], ['DH', 'AH', ' ', 'K', 'AA', 'M', 'AH', 'D', 'IY', ' ', 'AH', 'V', ' ', 'EH', 'R', 'ER', 'Z']]
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+ ```
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+
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+ ### Inference on GPU
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+ To perform inference on the GPU, add `run_opts={"device":"cuda"}` when calling the `from_hparams` method.
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+
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+ ### Limitations
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+ The SpeechBrain team does not provide any warranty on the performance achieved by this model when used on other datasets.
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+
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+ ### Training
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+ The model was trained with SpeechBrain (aa018540).
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+ To train it from scratch follows these steps:
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+ 1. Clone SpeechBrain:
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+ ```bash
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+ git clone https://github.com/speechbrain/speechbrain/
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+ ```
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+ 2. Install it:
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+ ```
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+ cd speechbrain
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+ pip install -r requirements.txt
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+ pip install -e .
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+ ```
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+
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+ 3. Run Training:
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+ ```
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+ cd recipes/LibriSpeech/G2P
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+ python train.py hparams/hparams_g2p_rnn.yaml --data_folder=your_data_folder
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+ ```
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+
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+ Adjust hyperparameters as needed by passing additional arguments.
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+
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+ # **Citing SpeechBrain**
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+ Please, cite SpeechBrain if you use it for your research or business.
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+
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+ ```bibtex
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+ @misc{speechbrain,
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+ title={{SpeechBrain}: A General-Purpose Speech Toolkit},
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+ author={Mirco Ravanelli and Titouan Parcollet and Peter Plantinga and Aku Rouhe and Samuele Cornell and Loren Lugosch and Cem Subakan and Nauman Dawalatabad and Abdelwahab Heba and Jianyuan Zhong and Ju-Chieh Chou and Sung-Lin Yeh and Szu-Wei Fu and Chien-Feng Liao and Elena Rastorgueva and François Grondin and William Aris and Hwidong Na and Yan Gao and Renato De Mori and Yoshua Bengio},
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+ year={2021},
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+ eprint={2106.04624},
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+ archivePrefix={arXiv},
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+ primaryClass={eess.AS},
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+ note={arXiv:2106.04624}
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+ }
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+ ```
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+
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+ Also please cite the SoundChoice G2P paper on which this pretrained model is based:
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+
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+ ```bibtex
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+ @misc{ploujnikov2022soundchoice,
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+ title={SoundChoice: Grapheme-to-Phoneme Models with Semantic Disambiguation},
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+ author={Artem Ploujnikov and Mirco Ravanelli},
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+ year={2022},
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+ eprint={2207.13703},
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+ archivePrefix={arXiv},
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+ primaryClass={cs.SD}
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+ }
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+ ```
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+
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+ # **About SpeechBrain**
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+ - Website: https://speechbrain.github.io/
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+ - Code: https://github.com/speechbrain/speechbrain/
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+ - HuggingFace: https://huggingface.co/speechbrain/
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+ {
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+ "speechbrain_interface": "GraphemeToPhoneme"
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+ }
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+ # Generated 2022-07-09 from:
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+ # /notebooks/speechbrain/recipes/LibriSpeech/G2P/hparams/hparams_g2p_rnn.yaml
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+ # yamllint disable
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+ # ################################
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+ # Model: LSTM (encoder) + GRU (decoder) (tokenized)
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+ # Authors:
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+ # Loren Lugosch & Mirco Ravanelli 2020
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+ # Artem Ploujnikov 2021
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+ # ################################
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+
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+ # Seed needs to be set at top of yaml, before objects with parameters are made
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+ seed: 1234
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+ __set_seed: !apply:torch.manual_seed [!ref <seed>]
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+
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+
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+ # Tokenizers
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+ char_tokenize: False
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+ char_token_type: unigram # ["unigram", "bpe", "char"]
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+ char_token_output: 512
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+ char_token_wordwise: True
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+ phn_tokenize: False
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+ phn_token_type: unigram # ["unigram", "bpe", "char"]
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+ phn_token_output: 512 # index(blank/eos/bos/unk) = 0
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+ phn_token_wordwise: True
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+ character_coverage: 1.0
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+
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+
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+ phonemes_count: 43
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+ graphemes_count: 31
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+ phonemes_enable_space: True
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+
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+ ctc_weight: 0.5
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+ ctc_window_size: 0
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+ homograph_loss_weight: 2.0
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+
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+ # Model parameters
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+ output_neurons: !apply:speechbrain.utils.hparams.choice
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+ value: !ref <phn_tokenize>
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+ choices:
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+ True: !ref <phn_token_output> + 1
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+ False: !ref <phonemes_count>
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+
43
+ enc_num_embeddings: !apply:speechbrain.utils.hparams.choice
44
+ value: !ref <char_tokenize>
45
+ choices:
46
+ True: !ref <char_token_output> + 1
47
+ False: !ref <graphemes_count>
48
+
49
+ enc_dropout: 0.5
50
+ enc_neurons: 512
51
+ enc_num_layers: 4
52
+ dec_dropout: 0.5
53
+ dec_neurons: 512
54
+ dec_att_neurons: 256
55
+ dec_num_layers: 4
56
+ embedding_dim: 512
57
+
58
+ # Determines whether to use BOS (beginning-of-sequence) or EOS (end-of-sequence) tokens
59
+ # Available modes:
60
+ # raw: no BOS/EOS tokens are added
61
+ # bos: a beginning-of-sequence token is added
62
+ # eos: an end-of-sequence token is added
63
+ grapheme_sequence_mode: bos
64
+ phoneme_sequence_mode: bos
65
+
66
+
67
+ # Special Token information
68
+ bos_index: 0
69
+ eos_index: 1
70
+ blank_index: 2
71
+ unk_index: 2
72
+ token_space_index: 512
73
+
74
+
75
+ # Language Model
76
+ lm_emb_dim: 256 # dimension of the embeddings
77
+ lm_rnn_size: 512 # dimension of hidden layers
78
+ lm_layers: 2 # number of hidden layers
79
+ lm_output_neurons: 43
80
+
81
+ # Beam Searcher
82
+ beam_search_min_decode_ratio: 0
83
+ beam_search_max_decode_ratio: 1.0
84
+ beam_search_beam_size: 16
85
+ beam_search_beam_size_valid: 16
86
+ beam_search_eos_threshold: 10.0
87
+ beam_search_using_max_attn_shift: false
88
+ beam_search_max_attn_shift: 10
89
+ beam_search_coverage_penalty: 5.0
90
+ beam_search_lm_weight: 0.5
91
+ beam_search_ctc_weight_decode: 0.4
92
+ beam_search_temperature: 1.25
93
+ beam_search_temperature_lm: 1.0
94
+
95
+ # Word embeddings
96
+ use_word_emb: true
97
+ word_emb_model: bert-base-uncased
98
+ word_emb_dim: 768
99
+ word_emb_enc_dim: 256
100
+ word_emb_norm_type: batch
101
+
102
+ graphemes:
103
+ - A
104
+ - B
105
+ - C
106
+ - D
107
+ - E
108
+ - F
109
+ - G
110
+ - H
111
+ - I
112
+ - J
113
+ - K
114
+ - L
115
+ - M
116
+ - N
117
+ - O
118
+ - P
119
+ - Q
120
+ - R
121
+ - S
122
+ - T
123
+ - U
124
+ - V
125
+ - W
126
+ - X
127
+ - Y
128
+ - Z
129
+ - "'"
130
+ - ' '
131
+
132
+ phonemes:
133
+ - AA
134
+ - AE
135
+ - AH
136
+ - AO
137
+ - AW
138
+ - AY
139
+ - B
140
+ - CH
141
+ - D
142
+ - DH
143
+ - EH
144
+ - ER
145
+ - EY
146
+ - F
147
+ - G
148
+ - HH
149
+ - IH
150
+ - IY
151
+ - JH
152
+ - K
153
+ - L
154
+ - M
155
+ - N
156
+ - NG
157
+ - OW
158
+ - OY
159
+ - P
160
+ - R
161
+ - S
162
+ - SH
163
+ - T
164
+ - TH
165
+ - UH
166
+ - UW
167
+ - V
168
+ - W
169
+ - Y
170
+ - Z
171
+ - ZH
172
+ - ' '
173
+
174
+ enc_input_dim: !apply:speechbrain.lobes.models.g2p.model.input_dim
175
+ use_word_emb: !ref <use_word_emb>
176
+ word_emb_enc_dim: !ref <word_emb_enc_dim>
177
+ embedding_dim: !ref <embedding_dim>
178
+
179
+ phn_char_map: !apply:speechbrain.lobes.models.g2p.dataio.build_token_char_map
180
+ tokens: !ref <phonemes>
181
+
182
+ char_phn_map: !apply:speechbrain.lobes.models.g2p.dataio.flip_map
183
+ map_dict: !ref <phn_char_map>
184
+
185
+ enc: !new:speechbrain.nnet.RNN.LSTM
186
+ input_shape: [null, null, !ref <enc_input_dim>]
187
+ bidirectional: True
188
+ hidden_size: !ref <enc_neurons>
189
+ num_layers: !ref <enc_num_layers>
190
+ dropout: !ref <enc_dropout>
191
+
192
+ lin: !new:speechbrain.nnet.linear.Linear
193
+ input_size: !ref <dec_neurons>
194
+ n_neurons: !ref <output_neurons>
195
+ bias: false
196
+
197
+ ctc_lin: !new:speechbrain.nnet.linear.Linear
198
+ input_size: !ref 2 * <enc_neurons>
199
+ n_neurons: !ref <output_neurons>
200
+
201
+ encoder_emb: !new:speechbrain.nnet.embedding.Embedding
202
+ num_embeddings: !ref <enc_num_embeddings>
203
+ embedding_dim: !ref <embedding_dim>
204
+
205
+ emb: !new:speechbrain.nnet.embedding.Embedding
206
+ num_embeddings: !ref <output_neurons>
207
+ embedding_dim: !ref <embedding_dim>
208
+
209
+ dec: !new:speechbrain.nnet.RNN.AttentionalRNNDecoder
210
+ enc_dim: !ref <enc_neurons> * 2
211
+ input_size: !ref <embedding_dim>
212
+ rnn_type: gru
213
+ attn_type: content
214
+ dropout: !ref <dec_dropout>
215
+ hidden_size: !ref <dec_neurons>
216
+ attn_dim: !ref <dec_att_neurons>
217
+ num_layers: !ref <dec_num_layers>
218
+
219
+ word_emb_enc: !new:speechbrain.lobes.models.g2p.model.WordEmbeddingEncoder
220
+ word_emb_dim: !ref <word_emb_dim>
221
+ word_emb_enc_dim: !ref <word_emb_enc_dim>
222
+ norm_type: batch
223
+
224
+ word_emb: !apply:speechbrain.lobes.models.g2p.dataio.lazy_init
225
+ init: !name:speechbrain.wordemb.transformer.TransformerWordEmbeddings
226
+ model: bert-base-uncased
227
+
228
+ log_softmax: !new:speechbrain.nnet.activations.Softmax
229
+ apply_log: true
230
+
231
+ model: !new:speechbrain.lobes.models.g2p.model.AttentionSeq2Seq
232
+ enc: !ref <enc>
233
+ encoder_emb: !ref <encoder_emb>
234
+ emb: !ref <emb>
235
+ dec: !ref <dec>
236
+ lin: !ref <lin>
237
+ out: !ref <log_softmax>
238
+ use_word_emb: !ref <use_word_emb>
239
+ word_emb_enc: !ref <word_emb_enc>
240
+
241
+ modules:
242
+ model: !ref <model>
243
+ enc: !ref <enc>
244
+ encoder_emb: !ref <encoder_emb>
245
+ emb: !ref <emb>
246
+ dec: !ref <dec>
247
+ lin: !ref <lin>
248
+ ctc_lin: !ref <ctc_lin>
249
+ out: !ref <log_softmax>
250
+ word_emb: !ref <word_emb>
251
+ word_emb_enc: !ref <word_emb_enc>
252
+
253
+ lm_model: !new:speechbrain.lobes.models.RNNLM.RNNLM
254
+ embedding_dim: !ref <lm_emb_dim>
255
+ rnn_layers: !ref <lm_layers>
256
+ rnn_neurons: !ref <lm_rnn_size>
257
+ output_neurons: !ref <lm_output_neurons>
258
+ return_hidden: True
259
+
260
+ ctc_scorer: !new:speechbrain.decoders.scorer.CTCScorer
261
+ eos_index: !ref <eos_index>
262
+ blank_index: !ref <blank_index>
263
+ ctc_fc: !ref <ctc_lin>
264
+ ctc_window_size: !ref <ctc_window_size>
265
+
266
+ coverage_scorer: !new:speechbrain.decoders.scorer.CoverageScorer
267
+ vocab_size: !ref <output_neurons>
268
+
269
+ scorer: !new:speechbrain.decoders.scorer.ScorerBuilder
270
+ full_scorers: [!ref <coverage_scorer>, !ref <ctc_scorer>]
271
+ weights:
272
+ coverage: !ref <beam_search_coverage_penalty>
273
+ ctc: !ref <ctc_weight>
274
+
275
+ beam_searcher: !new:speechbrain.decoders.S2SRNNBeamSearcher
276
+ embedding: !ref <emb>
277
+ decoder: !ref <dec>
278
+ linear: !ref <lin>
279
+ bos_index: !ref <bos_index>
280
+ eos_index: !ref <eos_index>
281
+ min_decode_ratio: !ref <beam_search_min_decode_ratio>
282
+ max_decode_ratio: !ref <beam_search_max_decode_ratio>
283
+ beam_size: !ref <beam_search_beam_size>
284
+ eos_threshold: !ref <beam_search_eos_threshold>
285
+ using_max_attn_shift: !ref <beam_search_using_max_attn_shift>
286
+ max_attn_shift: !ref <beam_search_max_attn_shift>
287
+ temperature: !ref <beam_search_temperature>
288
+ scorer: !ref <scorer>
289
+
290
+ beam_searcher_valid: !new:speechbrain.decoders.S2SRNNBeamSearcher
291
+ embedding: !ref <emb>
292
+ decoder: !ref <dec>
293
+ linear: !ref <lin>
294
+ bos_index: !ref <bos_index>
295
+ eos_index: !ref <eos_index>
296
+ min_decode_ratio: !ref <beam_search_min_decode_ratio>
297
+ max_decode_ratio: !ref <beam_search_max_decode_ratio>
298
+ beam_size: !ref <beam_search_beam_size>
299
+ eos_threshold: !ref <beam_search_eos_threshold>
300
+ using_max_attn_shift: !ref <beam_search_using_max_attn_shift>
301
+ max_attn_shift: !ref <beam_search_max_attn_shift>
302
+ temperature: !ref <beam_search_temperature>
303
+ scorer: !ref <scorer>
304
+
305
+ homograph_extractor: !new:speechbrain.lobes.models.g2p.homograph.SubsequenceExtractor
306
+
307
+ model_output_keys:
308
+ - p_seq
309
+ - char_lens
310
+ - encoder_out
311
+
312
+ grapheme_encoder: &id027 !new:speechbrain.dataio.encoder.TextEncoder
313
+ phoneme_encoder: &id024 !new:speechbrain.dataio.encoder.TextEncoder
314
+
315
+
316
+ grapheme_tokenizer: !apply:speechbrain.lobes.models.g2p.dataio.lazy_init
317
+ init: !name:speechbrain.tokenizers.SentencePiece.SentencePiece
318
+ model_dir: grapheme_tokenizer
319
+ bos_id: !ref <bos_index>
320
+ eos_id: !ref <eos_index>
321
+ unk_id: !ref <unk_index>
322
+ vocab_size: !ref <char_token_output>
323
+ annotation_train: null
324
+ annotation_read: char
325
+ model_type: !ref <char_token_type> # ["unigram", "bpe", "char"]
326
+ character_coverage: !ref <character_coverage>
327
+ annotation_format: json
328
+ text_file: grapheme_annotations.txt
329
+
330
+ phoneme_tokenizer: !apply:speechbrain.lobes.models.g2p.dataio.lazy_init
331
+ init: !name:speechbrain.tokenizers.SentencePiece.SentencePiece
332
+ model_dir: phoneme_tokenizer
333
+ bos_id: !ref <bos_index>
334
+ eos_id: !ref <eos_index>
335
+ unk_id: !ref <unk_index>
336
+ vocab_size: !ref <phn_token_output>
337
+ annotation_train: null
338
+ annotation_read: phn
339
+ model_type: !ref <phn_token_type> # ["unigram", "bpe", "char"]
340
+ character_coverage: !ref <character_coverage>
341
+ annotation_format: json
342
+ text_file: null
343
+
344
+ out_phoneme_decoder_tok: !apply:speechbrain.lobes.models.g2p.dataio.char_map_detokenize
345
+ tokenizer: !ref <phoneme_tokenizer>
346
+ char_map: !ref <char_phn_map>
347
+ token_space_index: !ref <token_space_index>
348
+ wordwise: !ref <phn_token_wordwise>
349
+
350
+ out_phoneme_decoder_raw: !name:speechbrain.lobes.models.g2p.dataio.text_decode
351
+ encoder: !ref <phoneme_encoder>
352
+
353
+ out_phoneme_decoder: !apply:speechbrain.utils.hparams.choice
354
+ value: false
355
+ choices:
356
+ True: !ref <out_phoneme_decoder_tok>
357
+ False: !ref <out_phoneme_decoder_raw>
358
+ encode_pipeline:
359
+ batch: false
360
+ use_padded_data: true
361
+ output_keys:
362
+ - grapheme_list
363
+ - grapheme_encoded_list
364
+ - grapheme_encoded
365
+ - word_emb
366
+ init:
367
+ - func: !name:speechbrain.lobes.models.g2p.dataio.enable_eos_bos
368
+ encoder: !ref <grapheme_encoder>
369
+ tokens: !ref <graphemes>
370
+ bos_index: !ref <bos_index>
371
+ eos_index: !ref <eos_index>
372
+ - func: !name:speechbrain.lobes.models.g2p.dataio.enable_eos_bos
373
+ encoder: !ref <phoneme_encoder>
374
+ tokens: !ref <phonemes>
375
+ bos_index: !ref <bos_index>
376
+ eos_index: !ref <eos_index>
377
+ steps:
378
+ - func: !name:speechbrain.lobes.models.g2p.dataio.clean_pipeline
379
+ graphemes: !ref <graphemes>
380
+ takes: txt
381
+ provides: txt_cleaned
382
+ - func: !name:speechbrain.lobes.models.g2p.dataio.grapheme_pipeline
383
+ grapheme_encoder: !ref <grapheme_encoder>
384
+ takes: txt_cleaned
385
+ provides:
386
+ - grapheme_list
387
+ - grapheme_encoded_list
388
+ - grapheme_encoded_raw
389
+
390
+ - func: !name:speechbrain.lobes.models.g2p.dataio.add_bos_eos
391
+ encoder: !ref <grapheme_encoder>
392
+ takes: grapheme_encoded_list
393
+ provides:
394
+ - grapheme_encoded
395
+ - grapheme_len
396
+ - grapheme_encoded_eos
397
+ - grapheme_len_eos
398
+ - func: !name:speechbrain.lobes.models.g2p.dataio.word_emb_pipeline
399
+ word_emb: !ref <word_emb>
400
+ grapheme_encoder: !ref <grapheme_encoder>
401
+ use_word_emb: !ref <use_word_emb>
402
+ takes:
403
+ - txt
404
+ - grapheme_encoded
405
+ - grapheme_len
406
+ provides: word_emb
407
+
408
+ decode_pipeline:
409
+ batch: true
410
+ output_keys:
411
+ - phonemes
412
+ steps:
413
+ - func: !name:speechbrain.lobes.models.g2p.dataio.beam_search_pipeline
414
+ beam_searcher: !ref <beam_searcher>
415
+ takes:
416
+ - char_lens
417
+ - encoder_out
418
+ provides:
419
+ - hyps
420
+ - scores
421
+ - func: !apply:speechbrain.utils.hparams.choice
422
+ value: false
423
+ choices:
424
+ True: !apply:speechbrain.lobes.models.g2p.dataio.char_map_detokenize
425
+ tokenizer: !ref <phoneme_tokenizer>
426
+ char_map: !ref <char_phn_map>
427
+ token_space_index: !ref <token_space_index>
428
+ wordwise: !ref <phn_token_wordwise>
429
+ False: !name:speechbrain.lobes.models.g2p.dataio.phoneme_decoder_pipeline
430
+ phoneme_encoder: !ref <phoneme_encoder>
431
+ takes:
432
+ - hyps
433
+ provides:
434
+ - phonemes
435
+
436
+
437
+ pretrainer: !new:speechbrain.utils.parameter_transfer.Pretrainer
438
+ loadables:
439
+ model: !ref <model>
440
+ ctc_lin: !ref <ctc_lin>
model.ckpt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:71bf7a7b290f88de5fdd7364fa4ab249bdd94a29e6cdc742ee6f69edeae64f61
3
+ size 128643257