DewiBrynJones commited on
Commit
28941b8
1 Parent(s): 5879b65

Upload README.md with huggingface_hub

Browse files
Files changed (1) hide show
  1. README.md +6 -37
README.md CHANGED
@@ -1,54 +1,22 @@
1
  ---
2
  language:
3
  - cy
 
4
  license: cc0-1.0
5
  size_categories:
6
  - 10K<n<100K
7
  pretty_name: Banc Trawsgrifiadau Bangor
8
  tags:
9
- - verbatim transcriptions
10
  - speech recognition
11
- dataset_info:
12
- features:
13
- - name: sentence
14
- dtype: string
15
- - name: audio
16
- dtype:
17
- audio:
18
- sampling_rate: 16000
19
- splits:
20
- - name: train
21
- num_bytes: 799672165.632
22
- num_examples: 35108
23
- - name: translations
24
- num_bytes: 24872333.0
25
- num_examples: 500
26
- - name: clips
27
- num_bytes: 887655970.904
28
- num_examples: 39009
29
- - name: test
30
- num_bytes: 88466601.992
31
- num_examples: 3901
32
- download_size: 1802523785
33
- dataset_size: 1800667071.528
34
- configs:
35
- - config_name: default
36
- data_files:
37
- - split: train
38
- path: data/train-*
39
- - split: translations
40
- path: data/translations-*
41
- - split: clips
42
- path: data/clips-*
43
- - split: test
44
- path: data/test-*
45
  ---
46
 
47
  [See below for English](#bangor-transcription-bank)
48
 
49
  # Banc Trawsgrifiadau Bangor
50
 
51
- Dyma fanc o 35 awr 39 munud a 53 eiliad o segmentau o leferydd naturiol dros hanner cant o gyfranwyr ar ffurf ffeiliau mp3, ynghyd â thrawsgrifiadau 'verbatim' cyfatebol o’r lleferydd ar ffurf ffeil .tsv. Mae'r mwyafrif o'r lleferydd yn leferydd digymell, naturiol. Dosbarthwn y deunydd hwn o dan drwydded agored CC0.
52
 
53
  ## Pwrpas
54
  Pwrpas y trawsgrifiadau hyn yw gweithredu fel data hyfforddi ar gyfer modelau adnabod lleferydd, gan gynnwys [ein modelau wav2vec](https://github.com/techiaith/docker-wav2vec2-cy). Ar gyfer y diben hwnnw, mae gofyn am drawsgrifiadau mwy verbatim o'r hyn a ddywedwyd na'r hyn a welir mewn trawsgrifiadau traddodiadol ac mewn isdeitlau, felly datblygwyd confensiwn arbennig ar gyfer y gwaith trawsgrifio ([gweler isod](#confensiynau_trawsgrifio)). Gydag ein modelau wav2vec, caiff cydran ychwnaegol, sef 'model iaith' ei defnyddio ar ôl y model adnabod lleferydd i safoni mwy ar allbwn y model iaith i fod yn debycach i drawsgrifiadau traddodiadol ac isdeitlau.
@@ -239,7 +207,7 @@ Diolchwn i'r cyfrannwyr am eu caniatâd i ddefnyddio'u lleferydd. Rydym hefyd yn
239
 
240
  # Bangor Transcription Bank
241
 
242
- This resource is a bank of 35 hours 39 minutes and 53 seconds of segments of natural speech from over 50 contributors in mp3 file format, together with corresponding 'verbatim' transcripts of the speech in .tsv file format. The majority of the speech is spontaneous, natural speech. We distribute this material under a CC0 open license.
243
 
244
  ## Purpose
245
  The purpose of these transcripts is to act as training data for speech recognition models, including [our wav2vec models](https://github.com/techiaith/docker-wav2vec2-cy). For that purpose, transcriptions are more verbatim than what is seen in traditional transcriptions and than what is required for subtitling purposes, thus a bespoke set of conventions has been developed for the transcription work ([see below](#transcription_conventions) ). Our wav2vec models use an auxiliary component, namely a 'language model', to further standardize the speech recognition model’s output in order that it be more similar to traditional transcriptions and subtitles.
@@ -418,3 +386,4 @@ In order to respect the contributors, by downloading this data you agree not to
418
 
419
  ## Acknowledgements
420
  We thank the contributors for their permission to use their speech. We are also grateful to the Welsh Government for funding this work as part of the Text, Speech and Translation Technology project for the Welsh Language.
 
 
1
  ---
2
  language:
3
  - cy
4
+ - en
5
  license: cc0-1.0
6
  size_categories:
7
  - 10K<n<100K
8
  pretty_name: Banc Trawsgrifiadau Bangor
9
  tags:
 
10
  - speech recognition
11
+ - verbatim transcriptions
12
+ - speech to translated text
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
13
  ---
14
 
15
  [See below for English](#bangor-transcription-bank)
16
 
17
  # Banc Trawsgrifiadau Bangor
18
 
19
+ Dyma fanc o 40 awr o segmentau o leferydd naturiol dros hanner cant o gyfranwyr ar ffurf ffeiliau mp3, ynghyd â thrawsgrifiadau 'verbatim' cyfatebol o’r lleferydd ar ffurf ffeil .tsv. Mae'r mwyafrif o'r lleferydd yn leferydd digymell, naturiol. Dosbarthwn y deunydd hwn o dan drwydded agored CC0.
20
 
21
  ## Pwrpas
22
  Pwrpas y trawsgrifiadau hyn yw gweithredu fel data hyfforddi ar gyfer modelau adnabod lleferydd, gan gynnwys [ein modelau wav2vec](https://github.com/techiaith/docker-wav2vec2-cy). Ar gyfer y diben hwnnw, mae gofyn am drawsgrifiadau mwy verbatim o'r hyn a ddywedwyd na'r hyn a welir mewn trawsgrifiadau traddodiadol ac mewn isdeitlau, felly datblygwyd confensiwn arbennig ar gyfer y gwaith trawsgrifio ([gweler isod](#confensiynau_trawsgrifio)). Gydag ein modelau wav2vec, caiff cydran ychwnaegol, sef 'model iaith' ei defnyddio ar ôl y model adnabod lleferydd i safoni mwy ar allbwn y model iaith i fod yn debycach i drawsgrifiadau traddodiadol ac isdeitlau.
 
207
 
208
  # Bangor Transcription Bank
209
 
210
+ This resource is a bank of 40 hours of segments of natural speech from over 50 contributors in mp3 file format, together with corresponding 'verbatim' transcripts of the speech in .tsv file format. The majority of the speech is spontaneous, natural speech. We distribute this material under a CC0 open license.
211
 
212
  ## Purpose
213
  The purpose of these transcripts is to act as training data for speech recognition models, including [our wav2vec models](https://github.com/techiaith/docker-wav2vec2-cy). For that purpose, transcriptions are more verbatim than what is seen in traditional transcriptions and than what is required for subtitling purposes, thus a bespoke set of conventions has been developed for the transcription work ([see below](#transcription_conventions) ). Our wav2vec models use an auxiliary component, namely a 'language model', to further standardize the speech recognition model’s output in order that it be more similar to traditional transcriptions and subtitles.
 
386
 
387
  ## Acknowledgements
388
  We thank the contributors for their permission to use their speech. We are also grateful to the Welsh Government for funding this work as part of the Text, Speech and Translation Technology project for the Welsh Language.
389
+