See https://github.com/k2-fsa/icefall/pull/1651

icefall-asr-ksponspeech-pruned-transducer-stateless7-streaming-2024-06-12

KsponSpeech is a large-scale spontaneous speech corpus of Korean. This corpus contains 969 hours of open-domain dialog utterances, spoken by about 2,000 native Korean speakers in a clean environment.

All data were constructed by recording the dialogue of two people freely conversing on a variety of topics and manually transcribing the utterances.

The transcription provides a dual transcription consisting of orthography and pronunciation, and disfluency tags for spontaneity of speech, such as filler words, repeated words, and word fragments.

The original audio data has a pcm extension. During preprocessing, it is converted into a file in the flac extension and saved anew.

KsponSpeech is publicly available on an open data hub site of the Korea government. The dataset must be downloaded manually.

For more details, please visit:

Streaming Zipformer-Transducer (Pruned Stateless Transducer + Streaming Zipformer)

Number of model parameters: 79,022,891, i.e., 79.02 M

Training on KsponSpeech (with MUSAN)

The CERs are:

decoding method	chunk size	eval_clean	eval_other	comment	decoding mode
greedy search	320ms	10.21	11.07	--epoch 30 --avg 9	simulated streaming
greedy search	320ms	10.22	11.07	--epoch 30 --avg 9	chunk-wise
fast beam search	320ms	10.21	11.04	--epoch 30 --avg 9	simulated streaming
fast beam search	320ms	10.25	11.08	--epoch 30 --avg 9	chunk-wise
modified beam search	320ms	10.13	10.88	--epoch 30 --avg 9	simulated streaming
modified beam search	320ms	10.1	10.93	--epoch 30 --avg 9	chunk-size
greedy search	640ms	9.94	10.82	--epoch 30 --avg 9	simulated streaming
greedy search	640ms	10.04	10.85	--epoch 30 --avg 9	chunk-wise
fast beam search	640ms	10.01	10.81	--epoch 30 --avg 9	simulated streaming
fast beam search	640ms	10.04	10.7	--epoch 30 --avg 9	chunk-wise
modified beam search	640ms	9.91	10.72	--epoch 30 --avg 9	simulated streaming
modified beam search	640ms	9.92	10.72	--epoch 30 --avg 9	chunk-size

Note: simulated streaming indicates feeding full utterance during decoding using decode.py, while chunk-size indicates feeding certain number of frames at each time using streaming_decode.py.