add some speech models & references (#405)

README.md

@@ -392,7 +392,7 @@
 
 |    |  アーキテクチャ  |  学習コーパス  |  開発元  | ライセンス |
 |:---|:---:|:---:|:---:|:---:|
-| [Kotoba-Whisper](https://huggingface.co/kotoba-tech/kotoba-whisper-v1.0)<br>([v1.0](https://huggingface.co/kotoba-tech/kotoba-whisper-v1.0), [v1.0-ggml](https://huggingface.co/kotoba-tech/kotoba-whisper-v1.0-ggml), [v1.0-faster](https://huggingface.co/kotoba-tech/kotoba-whisper-v1.0-faster), [v1.1](https://huggingface.co/kotoba-tech/kotoba-whisper-v1.1), [bilingual-v1.0](https://huggingface.co/kotoba-tech/kotoba-whisper-bilingual-v1.0), [bilingual-v1.0-ggml](https://huggingface.co/kotoba-tech/kotoba-whisper-bilingual-v1.0-ggml), [bilingual-v1.0-faster](https://huggingface.co/kotoba-tech/kotoba-whisper-bilingual-v1.0-faster), [v2.0](https://huggingface.co/kotoba-tech/kotoba-whisper-v2.0), [v2.0-ggml](https://huggingface.co/kotoba-tech/kotoba-whisper-v2.0-ggml), [v2.0-faster](https://huggingface.co/kotoba-tech/kotoba-whisper-v2.0-faster), [v2.1](https://huggingface.co/kotoba-tech/kotoba-whisper-v2.1)) | Distil-Whisper | ReazonSpeech<br>(+ Multilingual LibriSpeech) | Kotoba Technologies | Apache 2.0 |
+| [Kotoba-Whisper](https://huggingface.co/kotoba-tech/kotoba-whisper-v1.0)<br>([v1.0](https://huggingface.co/kotoba-tech/kotoba-whisper-v1.0), [v1.0-ggml](https://huggingface.co/kotoba-tech/kotoba-whisper-v1.0-ggml), [v1.0-faster](https://huggingface.co/kotoba-tech/kotoba-whisper-v1.0-faster), [v1.1](https://huggingface.co/kotoba-tech/kotoba-whisper-v1.1), [bilingual-v1.0](https://huggingface.co/kotoba-tech/kotoba-whisper-bilingual-v1.0), [bilingual-v1.0-ggml](https://huggingface.co/kotoba-tech/kotoba-whisper-bilingual-v1.0-ggml), [bilingual-v1.0-faster](https://huggingface.co/kotoba-tech/kotoba-whisper-bilingual-v1.0-faster), [v2.0](https://huggingface.co/kotoba-tech/kotoba-whisper-v2.0), [v2.0-ggml](https://huggingface.co/kotoba-tech/kotoba-whisper-v2.0-ggml), [v2.0-faster](https://huggingface.co/kotoba-tech/kotoba-whisper-v2.0-faster), [v2.1](https://huggingface.co/kotoba-tech/kotoba-whisper-v2.1), [v2.2](https://huggingface.co/kotoba-tech/kotoba-whisper-v2.2)) | Distil-Whisper | ReazonSpeech<br>(+ Multilingual LibriSpeech) | Kotoba Technologies | Apache 2.0 |
 | [Nue ASR](https://rinna.co.jp/news/2023/12/20231207.html)<br>([nue-asr](https://huggingface.co/rinna/nue-asr)) | Nue ASR<br>(HuBERT + LLM) | ReazonSpeech | rinna | Apache 2.0 |
 | [ReazonSpeech](https://research.reazon.jp/projects/ReazonSpeech/)<br>([espnet-v1](https://huggingface.co/reazon-research/reazonspeech-espnet-v1), [espnet-next](https://huggingface.co/reazon-research/reazonspeech-espnet-next), [espnet-v2](https://huggingface.co/reazon-research/reazonspeech-espnet-v2), [nemo-v2](https://huggingface.co/reazon-research/reazonspeech-nemo-v2)) | ESPnet (Conformer-Transducer) または NeMo (FastConformer-RNNT) | ReazonSpeech | レアゾン・ホールディングス | Apache 2.0 |
 
@@ -404,6 +404,8 @@
 | [Kotoba-Speech](https://huggingface.co/kotoba-tech/kotoba-speech-v0.1)<br>([v0.1](https://huggingface.co/kotoba-tech/kotoba-speech-v0.1)) | Transformer | 不明 | Kotoba Technologies | Apache 2.0 |
 | [東大HuBERT](https://huggingface.co/sarulab-speech/hubert-base-jtube)<br>([base-jtube](https://huggingface.co/sarulab-speech/hubert-base-jtube)) | HuBERT | JTubeSpeech | 東大 猿渡・高道研 | MIT |
 | [rinna HuBERT](https://rinna.co.jp/news/2023/04/20230428.html)<br>([base](https://huggingface.co/rinna/japanese-hubert-base), [large](https://huggingface.co/rinna/japanese-hubert-large)) | HuBERT | ReazonSpeech | rinna | Apache 2.0 |
+| [Reazon wav2vec 2.0](https://research.reazon.jp/blog/2024-10-21-Wav2Vec2-base-release.html)<br>([base](https://huggingface.co/reazon-research/japanese-wav2vec2-base), [large](https://huggingface.co/reazon-research/japanese-wav2vec2-large)) | wav2vec 2.0 | ReazonSpeech | レアゾン・ホールディングス | Apache 2.0 |
+| [rinna wav2vec 2.0](https://rinna.co.jp/news/2024/03/20240307.html)<br>([base](https://huggingface.co/rinna/japanese-wav2vec2-base)) | wav2vec 2.0 | ReazonSpeech | rinna | Apache 2.0 |
 
 <a id="benchmark-suites"></a>
 ## 日本語LLM評価ベンチマーク/データセットまとめ

en/README.md

@@ -390,7 +390,7 @@ Please point out any errors on the [issues page](https://github.com/llm-jp/aweso
 
 |    |  Architecture  |  Training Data  |  Developer  | License |
 |:---|:---:|:---:|:---:|:---:|
-| [Kotoba-Whisper](https://huggingface.co/kotoba-tech/kotoba-whisper-v1.0)<br>([v1.0](https://huggingface.co/kotoba-tech/kotoba-whisper-v1.0), [v1.0-ggml](https://huggingface.co/kotoba-tech/kotoba-whisper-v1.0-ggml), [v1.0-faster](https://huggingface.co/kotoba-tech/kotoba-whisper-v1.0-faster), [v1.1](https://huggingface.co/kotoba-tech/kotoba-whisper-v1.1), [bilingual-v1.0](https://huggingface.co/kotoba-tech/kotoba-whisper-bilingual-v1.0), [bilingual-v1.0-ggml](https://huggingface.co/kotoba-tech/kotoba-whisper-bilingual-v1.0-ggml), [bilingual-v1.0-faster](https://huggingface.co/kotoba-tech/kotoba-whisper-bilingual-v1.0-faster), [v2.0](https://huggingface.co/kotoba-tech/kotoba-whisper-v2.0), [v2.0-ggml](https://huggingface.co/kotoba-tech/kotoba-whisper-v2.0-ggml), [v2.0-faster](https://huggingface.co/kotoba-tech/kotoba-whisper-v2.0-faster), [v2.1](https://huggingface.co/kotoba-tech/kotoba-whisper-v2.1))  | Distil-Whisper | ReazonSpeech | Kotoba Technologies | Apache 2.0 |
+| [Kotoba-Whisper](https://huggingface.co/kotoba-tech/kotoba-whisper-v1.0)<br>([v1.0](https://huggingface.co/kotoba-tech/kotoba-whisper-v1.0), [v1.0-ggml](https://huggingface.co/kotoba-tech/kotoba-whisper-v1.0-ggml), [v1.0-faster](https://huggingface.co/kotoba-tech/kotoba-whisper-v1.0-faster), [v1.1](https://huggingface.co/kotoba-tech/kotoba-whisper-v1.1), [bilingual-v1.0](https://huggingface.co/kotoba-tech/kotoba-whisper-bilingual-v1.0), [bilingual-v1.0-ggml](https://huggingface.co/kotoba-tech/kotoba-whisper-bilingual-v1.0-ggml), [bilingual-v1.0-faster](https://huggingface.co/kotoba-tech/kotoba-whisper-bilingual-v1.0-faster), [v2.0](https://huggingface.co/kotoba-tech/kotoba-whisper-v2.0), [v2.0-ggml](https://huggingface.co/kotoba-tech/kotoba-whisper-v2.0-ggml), [v2.0-faster](https://huggingface.co/kotoba-tech/kotoba-whisper-v2.0-faster), [v2.1](https://huggingface.co/kotoba-tech/kotoba-whisper-v2.1), [v2.2](https://huggingface.co/kotoba-tech/kotoba-whisper-v2.2))  | Distil-Whisper | ReazonSpeech | Kotoba Technologies | Apache 2.0 |
 | [Nue ASR](https://rinna.co.jp/news/2023/12/20231207.html)<br>([nue-asr](https://huggingface.co/rinna/nue-asr)) | Nue ASR<br>(HuBERT + LLM) | ReazonSpeech | rinna | Apache 2.0 |
 | [ReazonSpeech](https://research.reazon.jp/projects/ReazonSpeech/)<br>([espnet-v1](https://huggingface.co/reazon-research/reazonspeech-espnet-v1), [espnet-next](https://huggingface.co/reazon-research/reazonspeech-espnet-next), [espnet-v2](https://huggingface.co/reazon-research/reazonspeech-espnet-v2), [nemo-v2](https://huggingface.co/reazon-research/reazonspeech-nemo-v2)) | ESPnet (Conformer-Transducer) / NeMo (FastConformer-RNNT) | ReazonSpeech | Reazon Holdings | Apache 2.0 |
 
@@ -402,6 +402,8 @@ Please point out any errors on the [issues page](https://github.com/llm-jp/aweso
 | [Kotoba-Speech](https://huggingface.co/kotoba-tech/kotoba-speech-v0.1)<br>([v0.1](https://huggingface.co/kotoba-tech/kotoba-speech-v0.1)) | Transformer | undisclosed | Kotoba Technologies | Apache 2.0 |
 | [UniversityOfTokyoHuBERT](https://huggingface.co/sarulab-speech/hubert-base-jtube)<br>([base-jtube](https://huggingface.co/sarulab-speech/hubert-base-jtube)) | HuBERT | JTubeSpeech | University of Tokyo<br>Saruwatari & Takamichi Lab | MIT |
 | [rinna HuBERT](https://rinna.co.jp/news/2023/04/20230428.html)<br>([base](https://huggingface.co/rinna/japanese-hubert-base), [large](https://huggingface.co/rinna/japanese-hubert-large)) | HuBERT | ReazonSpeech | rinna | Apache 2.0 |
+| [Reazon wav2vec 2.0](https://research.reazon.jp/blog/2024-10-21-Wav2Vec2-base-release.html)<br>([base](https://huggingface.co/reazon-research/japanese-wav2vec2-base), [large](https://huggingface.co/reazon-research/japanese-wav2vec2-large)) | wav2vec 2.0 | ReazonSpeech | Reazon Holdings | Apache 2.0 |
+| [rinna wav2vec 2.0](https://rinna.co.jp/news/2024/03/20240307.html)<br>([base](https://huggingface.co/rinna/japanese-wav2vec2-base)) | wav2vec 2.0 | ReazonSpeech | rinna | Apache 2.0 |
 
 <a id="benchmark-suites"></a>
 ## Evaluation Benchmarks for Japanese LLMs

fr/README.md

@@ -390,7 +390,7 @@ N'hésitez pas à signaler les erreurs sur la page [issues](https://github.com/l
 
 |    |  Architecture  |  Données d'entraînement  |  Développeur  | Licence |
 |:---|:---:|:---:|:---:|:---:|
-| [Kotoba-Whisper](https://huggingface.co/kotoba-tech/kotoba-whisper-v1.0)<br>([v1.0](https://huggingface.co/kotoba-tech/kotoba-whisper-v1.0), [v1.0-ggml](https://huggingface.co/kotoba-tech/kotoba-whisper-v1.0-ggml), [v1.0-faster](https://huggingface.co/kotoba-tech/kotoba-whisper-v1.0-faster), [v1.1](https://huggingface.co/kotoba-tech/kotoba-whisper-v1.1), [bilingual-v1.0](https://huggingface.co/kotoba-tech/kotoba-whisper-bilingual-v1.0), [bilingual-v1.0-ggml](https://huggingface.co/kotoba-tech/kotoba-whisper-bilingual-v1.0-ggml), [bilingual-v1.0-faster](https://huggingface.co/kotoba-tech/kotoba-whisper-bilingual-v1.0-faster), [v2.0](https://huggingface.co/kotoba-tech/kotoba-whisper-v2.0), [v2.0-ggml](https://huggingface.co/kotoba-tech/kotoba-whisper-v2.0-ggml), [v2.0-faster](https://huggingface.co/kotoba-tech/kotoba-whisper-v2.0-faster), [v2.1](https://huggingface.co/kotoba-tech/kotoba-whisper-v2.1)) | Distil-Whisper | ReazonSpeech | Kotoba Technologies | Apache 2.0 |
+| [Kotoba-Whisper](https://huggingface.co/kotoba-tech/kotoba-whisper-v1.0)<br>([v1.0](https://huggingface.co/kotoba-tech/kotoba-whisper-v1.0), [v1.0-ggml](https://huggingface.co/kotoba-tech/kotoba-whisper-v1.0-ggml), [v1.0-faster](https://huggingface.co/kotoba-tech/kotoba-whisper-v1.0-faster), [v1.1](https://huggingface.co/kotoba-tech/kotoba-whisper-v1.1), [bilingual-v1.0](https://huggingface.co/kotoba-tech/kotoba-whisper-bilingual-v1.0), [bilingual-v1.0-ggml](https://huggingface.co/kotoba-tech/kotoba-whisper-bilingual-v1.0-ggml), [bilingual-v1.0-faster](https://huggingface.co/kotoba-tech/kotoba-whisper-bilingual-v1.0-faster), [v2.0](https://huggingface.co/kotoba-tech/kotoba-whisper-v2.0), [v2.0-ggml](https://huggingface.co/kotoba-tech/kotoba-whisper-v2.0-ggml), [v2.0-faster](https://huggingface.co/kotoba-tech/kotoba-whisper-v2.0-faster), [v2.1](https://huggingface.co/kotoba-tech/kotoba-whisper-v2.1), [v2.2](https://huggingface.co/kotoba-tech/kotoba-whisper-v2.2)) | Distil-Whisper | ReazonSpeech | Kotoba Technologies | Apache 2.0 |
 | [Nue ASR](https://rinna.co.jp/news/2023/12/20231207.html)<br>([nue-asr](https://huggingface.co/rinna/nue-asr)) | Nue ASR<br>(HuBERT + LLM) | ReazonSpeech | rinna | Apache 2.0 |
 | [ReazonSpeech](https://research.reazon.jp/projects/ReazonSpeech/)<br>([espnet-v1](https://huggingface.co/reazon-research/reazonspeech-espnet-v1), [espnet-next](https://huggingface.co/reazon-research/reazonspeech-espnet-next), [espnet-v2](https://huggingface.co/reazon-research/reazonspeech-espnet-v2), [nemo-v2](https://huggingface.co/reazon-research/reazonspeech-nemo-v2)) | ESPnet (Conformer-Transducer) / NeMo (FastConformer-RNNT) | ReazonSpeech | Reazon Holdings | Apache 2.0 |
 
@@ -402,7 +402,8 @@ N'hésitez pas à signaler les erreurs sur la page [issues](https://github.com/l
 | [Kotoba-Speech](https://huggingface.co/kotoba-tech/kotoba-speech-v0.1)<br>([v0.1](https://huggingface.co/kotoba-tech/kotoba-speech-v0.1)) | Transformer | undisclosed | Kotoba Technologies | Apache 2.0 |
 | [UniversityOfTokyoHuBERT](https://huggingface.co/sarulab-speech/hubert-base-jtube)<br>([base-jtube](https://huggingface.co/sarulab-speech/hubert-base-jtube)) | HuBERT | JTubeSpeech | University of Tokyo<br>Saruwatari & Takamichi Lab | MIT |
 | [rinna HuBERT](https://rinna.co.jp/news/2023/04/20230428.html)<br>([base](https://huggingface.co/rinna/japanese-hubert-base), [large](https://huggingface.co/rinna/japanese-hubert-large)) | HuBERT | ReazonSpeech | rinna | Apache 2.0 |
-
+| [Reazon wav2vec 2.0](https://research.reazon.jp/blog/2024-10-21-Wav2Vec2-base-release.html)<br>([base](https://huggingface.co/reazon-research/japanese-wav2vec2-base), [large](https://huggingface.co/reazon-research/japanese-wav2vec2-large)) | wav2vec 2.0 | ReazonSpeech | Reazon Holdings | Apache 2.0 |
+| [rinna wav2vec 2.0](https://rinna.co.jp/news/2024/03/20240307.html)<br>([base](https://huggingface.co/rinna/japanese-wav2vec2-base)) | wav2vec 2.0 | ReazonSpeech | rinna | Apache 2.0 |
 
 <a id="benchmark-suites"></a>
 ## Standard d'évaluation pour les LLM en japonais

parts/references_model.md

@@ -17,6 +17,7 @@
 | Conformer | 2020.05.16 | INTERSPEECH 2020 | [Conformer: Convolution-augmented Transformer for Speech Recognition](https://arxiv.org/abs/2005.08100) |
 | GPT-3 | 2020.05.28 | NeurIPS 2020 | [Language Models are Few-Shot Learners](https://arxiv.org/abs/2005.14165) |
 | DeBERTa | 2020.06.05 | ICLR 2021 | [DeBERTa: Decoding-enhanced BERT with Disentangled Attention](https://arxiv.org/abs/2006.03654) |
+| wav2vec 2.0 | 2020.06.20 | NeurIPS 2020 | [wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations](https://arxiv.org/abs/2006.11477) |
 | BigBird | 2020.07.28 | NeurIPS 2020 | [Big Bird: Transformers for Longer Sequences](https://arxiv.org/abs/2007.14062) |
 | LUKE | 2020.10.02 | EMNLP 2020 | [LUKE: Deep Contextualized Entity Representations with Entity-aware Self-attention](https://aclanthology.org/2020.emnlp-main.523/) |
 | CLIP | 2021.02.26 | ICML 2021 | [Learning Transferable Visual Models From Natural Language Supervision](https://arxiv.org/abs/2103.00020) |
@@ -66,7 +67,7 @@
 | rinna GPT, rinna RoBERTa, Nekomata, Youri, etc. | 2024.04.02 | LREC-COLING 2024 | [Release of Pre-Trained Models for the Japanese Language](https://arxiv.org/abs/2404.01657) |
 | SambaLingo-Japanese | 2024.04.08 | - | [SambaLingo: Teaching Large Language Models New Languages](https://arxiv.org/abs/2404.05829) |
 | Heron | 2024.04.11 | - | [Heron-Bench: A Benchmark for Evaluating Vision Language Models in Japanese](https://arxiv.org/abs/2404.07824) |
-| Stockmark-13b | 2024.04.12 | - | [Pretraining and Updating Language- and Domain-specific Large Language Model: A Case Study in Japanese Business Domain](https://arxiv.org/abs/2404.08262) |
+| Stockmark-13b | 2024.04.12 | PACLIC 38 (2024) | [Pretraining and Updates of Domain-Specific LLM: A Case Study in the Japanese Business Domain](https://arxiv.org/abs/2404.08262) |
 | Phi-3 | 2024.04.22 | - | [Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone](https://arxiv.org/abs/2404.14219) |
 | InternVL 1.5 | 2024.04.25 | - | [How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites](https://arxiv.org/abs/2404.16821) |
 | Swallow | 2024.04.27 | COLM 2024 | [Continual Pre-Training for Cross-Lingual LLM Adaptation: Enhancing Japanese Language Capabilities](https://arxiv.org/abs/2404.17790) |