asahi417 commited on
Commit
d700b23
1 Parent(s): da47c7d

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +15 -1
README.md CHANGED
@@ -8,6 +8,11 @@ tags:
8
 
9
  # Cascaded Japanese Speech2Text Translation
10
  This is a pipeline for speech-to-text translation from Japanese speech to any target language text based on the cascaded approach, that consists of ASR and translation.
 
 
 
 
 
11
 
12
  ## Usage
13
  Here is an example to translate Japanese speech into English text translation.
@@ -24,7 +29,7 @@ from transformers import pipeline
24
  pipe = pipeline(
25
  model="japanese-asr/ja-cascaded-s2t-translation",
26
  model_kwargs={"attn_implementation": "sdpa"},
27
- model_translation="facebook/nllb-200-distilled-600M",
28
  tgt_lang="eng_Latn",
29
  chunk_length_s=15,
30
  trust_remote_code=True,
@@ -33,3 +38,12 @@ pipe = pipeline(
33
  # translate
34
  output = pipe("./sample_ja.flac")
35
  ```
 
 
 
 
 
 
 
 
 
 
8
 
9
  # Cascaded Japanese Speech2Text Translation
10
  This is a pipeline for speech-to-text translation from Japanese speech to any target language text based on the cascaded approach, that consists of ASR and translation.
11
+ The pipeline employs [kotoba-tech/kotoba-whisper-v2.0](https://huggingface.co/kotoba-tech/kotoba-whisper-v2.0) for ASR (Japanese speech -> Japanese text)
12
+ and [facebook/nllb-200-3.3B](https://huggingface.co/facebook/nllb-200-3.3B) for text translation.
13
+ The input must be Japanese speech, while the translation can be in any languages NLLB trained on. Please find the all available languages and their language codes
14
+ [here](https://github.com/facebookresearch/flores/blob/main/flores200/README.md#languages-in-flores-200).
15
+
16
 
17
  ## Usage
18
  Here is an example to translate Japanese speech into English text translation.
 
29
  pipe = pipeline(
30
  model="japanese-asr/ja-cascaded-s2t-translation",
31
  model_kwargs={"attn_implementation": "sdpa"},
32
+ model_translation="facebook/nllb-200-3.3B",
33
  tgt_lang="eng_Latn",
34
  chunk_length_s=15,
35
  trust_remote_code=True,
 
38
  # translate
39
  output = pipe("./sample_ja.flac")
40
  ```
41
+
42
+
43
+ Other NLLB models can be used by setting `model_translation` such as following.
44
+ - [facebook/nllb-200-3.3B](https://huggingface.co/facebook/nllb-200-3.3B)
45
+ - [facebook/nllb-200-distilled-600M](https://huggingface.co/facebook/nllb-200-distilled-600M)
46
+ - [facebook/nllb-200-distilled-1.3B](https://huggingface.co/facebook/nllb-200-distilled-1.3B)
47
+ - [facebook/nllb-200-1.3B](https://huggingface.co/facebook/nllb-200-1.3B)
48
+
49
+