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--- |
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license: apache-2.0 |
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language: |
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- ko |
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pipeline_tag: automatic-speech-recognition |
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tags: |
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- icefall |
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--- |
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See https://github.com/k2-fsa/icefall/pull/1651 |
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# icefall-asr-ksponspeech-pruned-transducer-stateless7-streaming-2024-06-12 |
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KsponSpeech is a large-scale spontaneous speech corpus of Korean. |
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This corpus contains 969 hours of open-domain dialog utterances, |
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spoken by about 2,000 native Korean speakers in a clean environment. |
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All data were constructed by recording the dialogue of two people |
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freely conversing on a variety of topics and manually transcribing the utterances. |
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The transcription provides a dual transcription consisting of orthography and pronunciation, |
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and disfluency tags for spontaneity of speech, such as filler words, repeated words, and word fragments. |
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The original audio data has a pcm extension. |
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During preprocessing, it is converted into a file in the flac extension and saved anew. |
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KsponSpeech is publicly available on an open data hub site of the Korea government. |
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The dataset must be downloaded manually. |
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For more details, please visit: |
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- Dataset: https://aihub.or.kr/aihubdata/data/view.do?currMenu=115&topMenu=100&aihubDataSe=realm&dataSetSn=123 |
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- Paper: https://www.mdpi.com/2076-3417/10/19/6936 |
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### Streaming Zipformer-Transducer (Pruned Stateless Transducer + Streaming Zipformer) |
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Number of model parameters: 79,022,891, i.e., 79.02 M |
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#### Training on KsponSpeech (with MUSAN) |
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The CERs are: |
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| decoding method | chunk size | eval_clean | eval_other | comment | decoding mode | |
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|----------------------|------------|------------|------------|---------------------|----------------------| |
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| greedy search | 320ms | 10.21 | 11.07 | --epoch 30 --avg 9 | simulated streaming | |
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| greedy search | 320ms | 10.22 | 11.07 | --epoch 30 --avg 9 | chunk-wise | |
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| fast beam search | 320ms | 10.21 | 11.04 | --epoch 30 --avg 9 | simulated streaming | |
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| fast beam search | 320ms | 10.25 | 11.08 | --epoch 30 --avg 9 | chunk-wise | |
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| modified beam search | 320ms | 10.13 | 10.88 | --epoch 30 --avg 9 | simulated streaming | |
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| modified beam search | 320ms | 10.1 | 10.93 | --epoch 30 --avg 9 | chunk-size | |
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| greedy search | 640ms | 9.94 | 10.82 | --epoch 30 --avg 9 | simulated streaming | |
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| greedy search | 640ms | 10.04 | 10.85 | --epoch 30 --avg 9 | chunk-wise | |
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| fast beam search | 640ms | 10.01 | 10.81 | --epoch 30 --avg 9 | simulated streaming | |
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| fast beam search | 640ms | 10.04 | 10.7 | --epoch 30 --avg 9 | chunk-wise | |
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| modified beam search | 640ms | 9.91 | 10.72 | --epoch 30 --avg 9 | simulated streaming | |
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| modified beam search | 640ms | 9.92 | 10.72 | --epoch 30 --avg 9 | chunk-size | |
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Note: `simulated streaming` indicates feeding full utterance during decoding using `decode.py`, |
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while `chunk-size` indicates feeding certain number of frames at each time using `streaming_decode.py`. |
