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README.md

@@ -7,49 +7,16 @@ size_categories:
 - 10K<n<100K
 pretty_name: Banc Trawsgrifiadau Bangor
 tags:
-- speech recognition
 - verbatim transcriptions
+- speech recognition
 - speech to translated text
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
-  - split: validation
-    path: data/validation-*
-  - split: test
-    path: data/test-*
-dataset_info:
-  features:
-  - name: sentence
-    dtype: string
-  - name: transcript
-    dtype: string
-  - name: normalized
-    dtype: string
-  - name: audio
-    dtype:
-      audio:
-        sampling_rate: 16000
-  splits:
-  - name: train
-    num_bytes: 852987862.144
-    num_examples: 37291
-  - name: validation
-    num_bytes: 86209017.336
-    num_examples: 3901
-  - name: test
-    num_bytes: 88802718.072
-    num_examples: 3901
-  download_size: 1009094981
-  dataset_size: 1027999597.552
 ---
 
 [See below for English](#bangor-transcription-bank)
 
 # Banc Trawsgrifiadau Bangor
 
-Dyma fanc o 45 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.
+Dyma fanc o 40 awr a 46 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.
 
 ## Pwrpas
 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.
@@ -240,7 +207,7 @@ Diolchwn i'r cyfrannwyr am eu caniatâd i ddefnyddio'u lleferydd. Rydym hefyd yn
 
 # Bangor Transcription Bank
 
-This resource is a bank of 45 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.
+This resource is a bank of 40 hours and 46 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.
 
 ## Purpose
 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.
@@ -419,4 +386,3 @@ In order to respect the contributors, by downloading this data you agree not to
 
 ## Acknowledgements 
 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.
-