Skip to content

Commit

Permalink
Add prefix beam search and corresponding decoding methods (#1786)
Browse files Browse the repository at this point in the history
* Add prefix beam search / shallow fussion / hotwords in librispeech ctc decode

* Add librispeech cr-ctc prefix beam search results
  • Loading branch information
pkufool authored Oct 30, 2024
1 parent 6c7863c commit d513d45
Show file tree
Hide file tree
Showing 4 changed files with 908 additions and 24 deletions.
9 changes: 6 additions & 3 deletions egs/librispeech/ASR/RESULTS.md
Original file line number Diff line number Diff line change
Expand Up @@ -153,6 +153,7 @@ You can use <https://github.com/k2-fsa/sherpa> to deploy it.
| decoding method | test-clean | test-other | comment |
|--------------------------------------|------------|------------|---------------------|
| ctc-greedy-decoding | 2.57 | 5.95 | --epoch 50 --avg 25 |
| ctc-prefix-beam-search | 2.52 | 5.85 | --epoch 50 --avg 25 |

The training command using 2 32G-V100 GPUs is:
```bash
Expand Down Expand Up @@ -184,7 +185,7 @@ export CUDA_VISIBLE_DEVICES="0,1"
The decoding command is:
```bash
export CUDA_VISIBLE_DEVICES="0"
for m in ctc-greedy-search; do
for m in ctc-greedy-search ctc-prefix-beam-search; do
./zipformer/ctc_decode.py \
--epoch 50 \
--avg 25 \
Expand Down Expand Up @@ -212,6 +213,7 @@ You can use <https://github.com/k2-fsa/sherpa> to deploy it.
| decoding method | test-clean | test-other | comment |
|--------------------------------------|------------|------------|---------------------|
| ctc-greedy-decoding | 2.12 | 4.62 | --epoch 50 --avg 24 |
| ctc-prefix-beam-search | 2.1 | 4.61 | --epoch 50 --avg 24 |

The training command using 4 32G-V100 GPUs is:
```bash
Expand All @@ -238,7 +240,7 @@ export CUDA_VISIBLE_DEVICES="0,1,2,3"
The decoding command is:
```bash
export CUDA_VISIBLE_DEVICES="0"
for m in ctc-greedy-search; do
for m in ctc-greedy-search ctc-prefix-beam-search; do
./zipformer/ctc_decode.py \
--epoch 50 \
--avg 24 \
Expand All @@ -262,6 +264,7 @@ You can use <https://github.com/k2-fsa/sherpa> to deploy it.
| decoding method | test-clean | test-other | comment |
|--------------------------------------|------------|------------|---------------------|
| ctc-greedy-decoding | 2.03 | 4.37 | --epoch 50 --avg 26 |
| ctc-prefix-beam-search | 2.02 | 4.35 | --epoch 50 --avg 26 |

The training command using 2 80G-A100 GPUs is:
```bash
Expand Down Expand Up @@ -292,7 +295,7 @@ export CUDA_VISIBLE_DEVICES="0,1"
The decoding command is:
```bash
export CUDA_VISIBLE_DEVICES="0"
for m in ctc-greedy-search; do
for m in ctc-greedy-search ctc-prefix-beam-search; do
./zipformer/ctc_decode.py \
--epoch 50 \
--avg 26 \
Expand Down
Loading

0 comments on commit d513d45

Please sign in to comment.