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zr_jin c3f6f28116
Zipformer recipe for Cantonese dataset MDCC (#1537) 
* init commit

* Create README.md

* handle code switching cases

* misc. fixes

* added manifest statistics

* init commit for the zipformer recipe

* added scripts for exporting model

* added RESULTS.md

* added scripts for streaming related stuff

* doc str fixed
2024-03-13 10:01:28 +08:00
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Zipformer recipe for Cantonese dataset MDCC (#1537)
2024-03-13 10:01:28 +08:00
zipformer
Zipformer recipe for Cantonese dataset MDCC (#1537)
2024-03-13 10:01:28 +08:00
prepare.sh
Zipformer recipe for Cantonese dataset MDCC (#1537)
2024-03-13 10:01:28 +08:00
README.md
Zipformer recipe for Cantonese dataset MDCC (#1537)
2024-03-13 10:01:28 +08:00
RESULTS.md
Zipformer recipe for Cantonese dataset MDCC (#1537)
2024-03-13 10:01:28 +08:00
shared
Zipformer recipe for Cantonese dataset MDCC (#1537)
2024-03-13 10:01:28 +08:00

README.md

Introduction

Multi-Domain Cantonese Corpus (MDCC), consists of 73.6 hours of clean read speech paired with transcripts, collected from Cantonese audiobooks from Hong Kong. It comprises philosophy, politics, education, culture, lifestyle and family domains, covering a wide range of topics.

Manuscript can be found at: https://arxiv.org/abs/2201.02419

Transducers

Encoder Decoder Comment
zipformer Upgraded Zipformer Embedding + Conv1d The latest recipe with context-size set to 1

The decoder is modified from the paper Rnn-Transducer with Stateless Prediction Network. We place an additional Conv1d layer right after the input embedding layer.