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icefall/egs/mdcc/ASR
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Fangjun Kuang 63563d16d3
Fix setting joiner dim (#2027) 
Fixes incorrect computation of encoder_dim when encoder_dim is a comma-separated list of integers by ensuring numeric (not lexicographic) max is used.

Fixes #2018

- Replace int(max(params.encoder_dim.split(","))) (lexicographic max on strings) with max(_to_int_tuple(params.encoder_dim)) (numeric max).
- Apply the fix consistently across all affected training scripts.
2025-09-19 09:42:41 +08:00
..
local
Zipformer recipe for Cantonese dataset MDCC (#1537)
2024-03-13 10:01:28 +08:00
zipformer
Fix setting joiner dim (#2027)
2025-09-19 09:42:41 +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.