diff --git a/README.md b/README.md index 64d6d894a..f0cbfa87f 100644 --- a/README.md +++ b/README.md @@ -22,7 +22,7 @@ ## What's new: ### Multi-Channel Multi-Party Meeting Transcription 2.0 (M2MET2.0) Challenge -We are pleased to announce that the M2MeT2.0 challenge will be held in the near future. The baseline system is conducted on FunASR and is provided as a receipe of AliMeeting corpus. For more details you can see the guidence of M2MET2.0 ([CN](https://alibaba-damo-academy.github.io/FunASR/m2met2_cn/index.html)/[EN](https://alibaba-damo-academy.github.io/FunASR/m2met2/index.html)). +We are pleased to announce that the M2MeT2.0 challenge has been accepted by the ASRU2023 challenge special session. The registration is now open. The baseline system is conducted on FunASR and is provided as a receipe of AliMeeting corpus. For more details you can see the guidence of M2MET2.0 ([CN](https://alibaba-damo-academy.github.io/FunASR/m2met2_cn/index.html)/[EN](https://alibaba-damo-academy.github.io/FunASR/m2met2/index.html)). ### Release notes For the release notes, please ref to [news](https://github.com/alibaba-damo-academy/FunASR/releases) diff --git a/docs/m2met2/Baseline.md b/docs/m2met2/Baseline.md index 6f9609bde..a7820863f 100644 --- a/docs/m2met2/Baseline.md +++ b/docs/m2met2/Baseline.md @@ -1,11 +1,31 @@ # Baseline ## Overview -We will release an E2E SA-ASR~\cite{kanda21b_interspeech} baseline conducted on [FunASR](https://github.com/alibaba-damo-academy/FunASR) at the time according to the timeline. The model architecture is shown in Figure 3. The SpeakerEncoder is initialized with a pre-trained speaker verification model from ModelScope. This speaker verification model is also be used to extract the speaker embedding in the speaker profile. +We will release an E2E SA-ASR baseline conducted on [FunASR](https://github.com/alibaba-damo-academy/FunASR) at the time according to the timeline. The model architecture is shown in Figure 3. The SpeakerEncoder is initialized with a pre-trained speaker verification model from ModelScope. This speaker verification model is also be used to extract the speaker embedding in the speaker profile. ![model archietecture](images/sa_asr_arch.png) ## Quick start -#TODO: fill with the README.md of the baseline +To run the baseline, first you need to install FunASR and ModelScope. ([installation](https://alibaba-damo-academy.github.io/FunASR/en/installation.html)) +There are two startup scripts, `run.sh` for training and evaluating on the old eval and test sets, and `run_m2met_2023_infer.sh` for inference on the new test set of the Multi-Channel Multi-Party Meeting Transcription 2.0 ([M2MET2.0](https://alibaba-damo-academy.github.io/FunASR/m2met2/index.html)) Challenge. +Before running `run.sh`, you must manually download and unpack the [AliMeeting](http://www.openslr.org/119/) corpus and place it in the `./dataset` directory: +```shell +dataset +|—— Eval_Ali_far +|—— Eval_Ali_near +|—— Test_Ali_far +|—— Test_Ali_near +|—— Train_Ali_far +|—— Train_Ali_near +Before running `run_m2met_2023_infer.sh`, you need to place the new test set `Test_2023_Ali_far` (to be released after the challenge starts) in the `./dataset` directory, which contains only raw audios. Then put the given `wav.scp`, `wav_raw.scp`, `segments`, `utt2spk` and `spk2utt` in the `./data/Test_2023_Ali_far` directory. +```shell +data/Test_2023_Ali_far +|—— wav.scp +|—— wav_raw.scp +|—— segments +|—— utt2spk +|—— spk2utt +``` +For more details you can see [here](https://github.com/alibaba-damo-academy/FunASR/blob/main/egs/alimeeting/sa-asr/README.md) ## Baseline results The results of the baseline system are shown in Table 3. The speaker profile adopts the oracle speaker embedding during training. However, due to the lack of oracle speaker label during evaluation, the speaker profile provided by an additional spectral clustering is used. Meanwhile, the results of using the oracle speaker profile on Eval and Test Set are also provided to show the impact of speaker profile accuracy. diff --git a/docs/m2met2/Introduction.md b/docs/m2met2/Introduction.md index 99a426f2a..a00122a47 100644 --- a/docs/m2met2/Introduction.md +++ b/docs/m2met2/Introduction.md @@ -13,15 +13,15 @@ Building on the success of the previous M2MeT challenge, we are excited to propo - $ May~8, 2023: $ Baseline release. - $ May~15, 2023: $ Registration deadline, the due date for participants to join the Challenge. - $ June~9, 2023: $ Test data release and leaderboard open. -- $ June~13, 2023: $ Final submission deadline. +- $ June~13, 2023: $ Final submission deadline and leaderboar close. - $ June~19, 2023: $ Evaluation result and ranking release. - $ July~3, 2023: $ Deadline for paper submission. - $ July~10, 2023: $ Deadline for final paper submission. -- $ December~12\ to\ 16, 2023: $ ASRU Workshop and challenge session +- $ December~12\ to\ 16, 2023: $ ASRU Workshop and challenge Session ## Guidelines -Interested participants, whether from academia or industry, must register for the challenge by completing the Google form below. The deadline for registration is May 15, 2023. +Interested participants, whether from academia or industry, must register for the challenge by completing the Google form below. The deadline for registration is May 22, 2023. Participants are also welcome to join the [wechat group](https://alibaba-damo-academy.github.io/FunASR/m2met2/Contact.html) of M2MET2.0 and keep up to date with the latest updates about the challenge. [M2MET2.0 Registration](https://docs.google.com/forms/d/e/1FAIpQLSf77T9vAl7Ym-u5g8gXu18SBofoWRaFShBo26Ym0-HDxHW9PQ/viewform?usp=sf_link) diff --git a/docs/m2met2/_build/doctrees/Baseline.doctree b/docs/m2met2/_build/doctrees/Baseline.doctree index 9fc7c50bc..b2577644c 100644 Binary files a/docs/m2met2/_build/doctrees/Baseline.doctree and b/docs/m2met2/_build/doctrees/Baseline.doctree differ diff --git a/docs/m2met2/_build/doctrees/Introduction.doctree b/docs/m2met2/_build/doctrees/Introduction.doctree index f44d936c0..b3a25f1ef 100644 Binary files a/docs/m2met2/_build/doctrees/Introduction.doctree and b/docs/m2met2/_build/doctrees/Introduction.doctree differ diff --git a/docs/m2met2/_build/doctrees/environment.pickle b/docs/m2met2/_build/doctrees/environment.pickle index a71853ab4..6abb44828 100644 Binary files a/docs/m2met2/_build/doctrees/environment.pickle and b/docs/m2met2/_build/doctrees/environment.pickle differ diff --git a/docs/m2met2/_build/html/.buildinfo b/docs/m2met2/_build/html/.buildinfo index d62b4cf37..97d32c4e5 100644 --- a/docs/m2met2/_build/html/.buildinfo +++ b/docs/m2met2/_build/html/.buildinfo @@ -1,4 +1,4 @@ # Sphinx build info version 1 # This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done. -config: 9907eab6bf227ca0fc6db297f26919da +config: a62852d90c3e533904d811bbf85f977d tags: 645f666f9bcd5a90fca523b33c5a78b7 diff --git a/docs/m2met2/_build/html/Baseline.html b/docs/m2met2/_build/html/Baseline.html index e52d32275..4f91c6b88 100644 --- a/docs/m2met2/_build/html/Baseline.html +++ b/docs/m2met2/_build/html/Baseline.html @@ -15,7 +15,7 @@ - Baseline — m2met2 documentation + Baseline — MULTI-PARTY MEETING TRANSCRIPTION CHALLENGE 2.0 @@ -44,7 +44,7 @@
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    diff --git a/docs/m2met2/_build/html/Contact.html b/docs/m2met2/_build/html/Contact.html index c1f69e317..5fc44d108 100644 --- a/docs/m2met2/_build/html/Contact.html +++ b/docs/m2met2/_build/html/Contact.html @@ -15,7 +15,7 @@ - Contact — m2met2 documentation + Contact — MULTI-PARTY MEETING TRANSCRIPTION CHALLENGE 2.0 @@ -40,7 +40,7 @@
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    diff --git a/docs/m2met2/_build/html/Introduction.html b/docs/m2met2/_build/html/Introduction.html index c89e665fa..6100fe61c 100644 --- a/docs/m2met2/_build/html/Introduction.html +++ b/docs/m2met2/_build/html/Introduction.html @@ -15,7 +15,7 @@ - Introduction — m2met2 documentation + Introduction — MULTI-PARTY MEETING TRANSCRIPTION CHALLENGE 2.0 @@ -45,7 +45,7 @@
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    diff --git a/docs/m2met2/_build/html/_images/qrcode.png b/docs/m2met2/_build/html/_images/qrcode.png index 68984beac..54b2f55d2 100644 Binary files a/docs/m2met2/_build/html/_images/qrcode.png and b/docs/m2met2/_build/html/_images/qrcode.png differ diff --git a/docs/m2met2/_build/html/_sources/Baseline.md.txt b/docs/m2met2/_build/html/_sources/Baseline.md.txt index 6f9609bde..a7820863f 100644 --- a/docs/m2met2/_build/html/_sources/Baseline.md.txt +++ b/docs/m2met2/_build/html/_sources/Baseline.md.txt @@ -1,11 +1,31 @@ # Baseline ## Overview -We will release an E2E SA-ASR~\cite{kanda21b_interspeech} baseline conducted on [FunASR](https://github.com/alibaba-damo-academy/FunASR) at the time according to the timeline. The model architecture is shown in Figure 3. The SpeakerEncoder is initialized with a pre-trained speaker verification model from ModelScope. This speaker verification model is also be used to extract the speaker embedding in the speaker profile. +We will release an E2E SA-ASR baseline conducted on [FunASR](https://github.com/alibaba-damo-academy/FunASR) at the time according to the timeline. The model architecture is shown in Figure 3. The SpeakerEncoder is initialized with a pre-trained speaker verification model from ModelScope. This speaker verification model is also be used to extract the speaker embedding in the speaker profile. ![model archietecture](images/sa_asr_arch.png) ## Quick start -#TODO: fill with the README.md of the baseline +To run the baseline, first you need to install FunASR and ModelScope. ([installation](https://alibaba-damo-academy.github.io/FunASR/en/installation.html)) +There are two startup scripts, `run.sh` for training and evaluating on the old eval and test sets, and `run_m2met_2023_infer.sh` for inference on the new test set of the Multi-Channel Multi-Party Meeting Transcription 2.0 ([M2MET2.0](https://alibaba-damo-academy.github.io/FunASR/m2met2/index.html)) Challenge. +Before running `run.sh`, you must manually download and unpack the [AliMeeting](http://www.openslr.org/119/) corpus and place it in the `./dataset` directory: +```shell +dataset +|—— Eval_Ali_far +|—— Eval_Ali_near +|—— Test_Ali_far +|—— Test_Ali_near +|—— Train_Ali_far +|—— Train_Ali_near +Before running `run_m2met_2023_infer.sh`, you need to place the new test set `Test_2023_Ali_far` (to be released after the challenge starts) in the `./dataset` directory, which contains only raw audios. Then put the given `wav.scp`, `wav_raw.scp`, `segments`, `utt2spk` and `spk2utt` in the `./data/Test_2023_Ali_far` directory. +```shell +data/Test_2023_Ali_far +|—— wav.scp +|—— wav_raw.scp +|—— segments +|—— utt2spk +|—— spk2utt +``` +For more details you can see [here](https://github.com/alibaba-damo-academy/FunASR/blob/main/egs/alimeeting/sa-asr/README.md) ## Baseline results The results of the baseline system are shown in Table 3. The speaker profile adopts the oracle speaker embedding during training. However, due to the lack of oracle speaker label during evaluation, the speaker profile provided by an additional spectral clustering is used. Meanwhile, the results of using the oracle speaker profile on Eval and Test Set are also provided to show the impact of speaker profile accuracy. diff --git a/docs/m2met2/_build/html/_sources/Introduction.md.txt b/docs/m2met2/_build/html/_sources/Introduction.md.txt index 99a426f2a..a00122a47 100644 --- a/docs/m2met2/_build/html/_sources/Introduction.md.txt +++ b/docs/m2met2/_build/html/_sources/Introduction.md.txt @@ -13,15 +13,15 @@ Building on the success of the previous M2MeT challenge, we are excited to propo - $ May~8, 2023: $ Baseline release. - $ May~15, 2023: $ Registration deadline, the due date for participants to join the Challenge. - $ June~9, 2023: $ Test data release and leaderboard open. -- $ June~13, 2023: $ Final submission deadline. +- $ June~13, 2023: $ Final submission deadline and leaderboar close. - $ June~19, 2023: $ Evaluation result and ranking release. - $ July~3, 2023: $ Deadline for paper submission. - $ July~10, 2023: $ Deadline for final paper submission. -- $ December~12\ to\ 16, 2023: $ ASRU Workshop and challenge session +- $ December~12\ to\ 16, 2023: $ ASRU Workshop and challenge Session ## Guidelines -Interested participants, whether from academia or industry, must register for the challenge by completing the Google form below. The deadline for registration is May 15, 2023. +Interested participants, whether from academia or industry, must register for the challenge by completing the Google form below. The deadline for registration is May 22, 2023. Participants are also welcome to join the [wechat group](https://alibaba-damo-academy.github.io/FunASR/m2met2/Contact.html) of M2MET2.0 and keep up to date with the latest updates about the challenge. [M2MET2.0 Registration](https://docs.google.com/forms/d/e/1FAIpQLSf77T9vAl7Ym-u5g8gXu18SBofoWRaFShBo26Ym0-HDxHW9PQ/viewform?usp=sf_link) diff --git a/docs/m2met2/_build/html/genindex.html b/docs/m2met2/_build/html/genindex.html index e7e17b6ed..b331f6f87 100644 --- a/docs/m2met2/_build/html/genindex.html +++ b/docs/m2met2/_build/html/genindex.html @@ -14,7 +14,7 @@ - Index — m2met2 documentation + Index — MULTI-PARTY MEETING TRANSCRIPTION CHALLENGE 2.0 @@ -35,7 +35,7 @@
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\ No newline at end of file diff --git a/docs/m2met2/conf.py b/docs/m2met2/conf.py index 19b93f5b3..9b2a9b57d 100644 --- a/docs/m2met2/conf.py +++ b/docs/m2met2/conf.py @@ -7,7 +7,7 @@ import guzzle_sphinx_theme # -- Project information ----------------------------------------------------- # https://www.sphinx-doc.org/en/master/usage/configuration.html#project-information -project = 'm2met2' +project = 'MULTI-PARTY MEETING TRANSCRIPTION CHALLENGE 2.0' copyright = '2023, Speech Lab, Alibaba Group; ASLP Group, Northwestern Polytechnical University' author = 'Speech Lab, Alibaba Group; Audio, Speech and Language Processing Group, Northwestern Polytechnical University' diff --git a/docs/m2met2/images/qrcode.png b/docs/m2met2/images/qrcode.png index 68984beac..54b2f55d2 100644 Binary files a/docs/m2met2/images/qrcode.png and b/docs/m2met2/images/qrcode.png differ diff --git a/docs/m2met2_cn/_build/doctrees/environment.pickle b/docs/m2met2_cn/_build/doctrees/environment.pickle index bb82bcbbe..e3a184d38 100644 Binary files a/docs/m2met2_cn/_build/doctrees/environment.pickle and b/docs/m2met2_cn/_build/doctrees/environment.pickle differ diff --git a/docs/m2met2_cn/_build/doctrees/基线.doctree b/docs/m2met2_cn/_build/doctrees/基线.doctree index f88f67d87..f33c2e133 100644 Binary files a/docs/m2met2_cn/_build/doctrees/基线.doctree and b/docs/m2met2_cn/_build/doctrees/基线.doctree differ diff --git a/docs/m2met2_cn/_build/doctrees/简介.doctree b/docs/m2met2_cn/_build/doctrees/简介.doctree index 26017348b..b7f635a1a 100644 Binary files a/docs/m2met2_cn/_build/doctrees/简介.doctree and b/docs/m2met2_cn/_build/doctrees/简介.doctree differ diff --git a/docs/m2met2_cn/_build/html/.buildinfo b/docs/m2met2_cn/_build/html/.buildinfo index 6b8368e2f..35632ee02 100644 --- a/docs/m2met2_cn/_build/html/.buildinfo +++ b/docs/m2met2_cn/_build/html/.buildinfo @@ -1,4 +1,4 @@ # Sphinx build info version 1 # This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done. -config: 5462207d1656a9ae4ca43c2890d094be +config: 06d9c1d4093817b45b9d4df7ab350eaf tags: 645f666f9bcd5a90fca523b33c5a78b7 diff --git a/docs/m2met2_cn/_build/html/_images/qrcode.png b/docs/m2met2_cn/_build/html/_images/qrcode.png index 68984beac..54b2f55d2 100644 Binary files a/docs/m2met2_cn/_build/html/_images/qrcode.png and b/docs/m2met2_cn/_build/html/_images/qrcode.png differ diff --git a/docs/m2met2_cn/_build/html/_sources/基线.md.txt b/docs/m2met2_cn/_build/html/_sources/基线.md.txt index e4d02f72e..4b031beee 100644 --- a/docs/m2met2_cn/_build/html/_sources/基线.md.txt +++ b/docs/m2met2_cn/_build/html/_sources/基线.md.txt @@ -5,8 +5,27 @@ ![model archietecture](images/sa_asr_arch.png) ## 快速开始 -#TODO: fill with the README.md of the baseline - +首先需要安装FunASR和ModelScope. ([installation](https://alibaba-damo-academy.github.io/FunASR/en/installation.html)) +基线系统有训练和测试两个脚本，`run.sh` 是用于训练基线系统并在M2MET的验证与测试集上评估的，而 `run_m2met_2023_infer.sh` 用于此次竞赛预备开放的全新测试集上测试同时生成符合竞赛最终提交格式的文件。 +在运行 `run.sh`前，需要自行下载并解压[AliMeeting](http://www.openslr.org/119/)数据集并放置于`./dataset`目录下： +```shell +dataset +|—— Eval_Ali_far +|—— Eval_Ali_near +|—— Test_Ali_far +|—— Test_Ali_near +|—— Train_Ali_far +|—— Train_Ali_near +在运行 `run_m2met_2023_infer.sh`前, 需要将测试集`Test_2023_Ali_far`（仅包含音频，将于6.16发布）放置于`./dataset`目录下。然后将主办方提供的`wav.scp`，`wav_raw.scp`，`segments`，`utt2spk`和`spk2utt`放置于`./data/Test_2023_Ali_far`目录下。 +```shell +data/Test_2023_Ali_far +|—— wav.scp +|—— wav_raw.scp +|—— segments +|—— utt2spk +|—— spk2utt +``` +更多基线系统详情见[此处](https://github.com/alibaba-damo-academy/FunASR/blob/main/egs/alimeeting/sa-asr/README.md) ## 基线结果 基线系统的结果如表3所示。在训练期间，说话人档案采用了真实说话人嵌入。然而由于在评估过程中缺乏真实说话人标签，因此使用了由额外的谱聚类提供的说话人特征。同时我们还提供了在评估和测试集上使用真实说话人档案的结果，以显示说话人档案准确性的影响。 ![baseline result](images/baseline_result.png) \ No newline at end of file diff --git a/docs/m2met2_cn/_build/html/_sources/简介.md.txt b/docs/m2met2_cn/_build/html/_sources/简介.md.txt index 5afb6a099..7f2925bf3 100644 --- a/docs/m2met2_cn/_build/html/_sources/简介.md.txt +++ b/docs/m2met2_cn/_build/html/_sources/简介.md.txt @@ -1,5 +1,6 @@ # 简介 ## 竞赛介绍 + 语音识别（Automatic Speech Recognition）、说话人日志（Speaker Diarization）等语音处理技术的最新发展激发了众多智能语音的广泛应用。然而会议场景由于其复杂的声学条件和不同的讲话风格，包括重叠的讲话、不同数量的发言者、大会议室的远场信号以及环境噪声和混响，仍然属于一项极具挑战性的任务。 为了推动会议场景语音识别的发展，已经有很多相关的挑战赛，如 Rich Transcription evaluation 和 CHIME（Computational Hearing in Multisource Environments） 挑战赛。最新的CHIME挑战赛关注于远距离自动语音识别和开发能在各种不同拓扑结构的阵列和应用场景中通用的系统。然而不同语言之间的差异限制了非英语会议转录的进展。MISP（Multimodal Information Based Speech Processing）和M2MeT（Multi-Channel Multi-Party Meeting Transcription）挑战赛为推动普通话会议场景语音识别做出了贡献。MISP挑战赛侧重于用视听多模态的方法解决日常家庭环境中的远距离多麦克风信号处理问题，而M2MeT挑战则侧重于解决离线会议室中会议转录的语音重叠问题。 @@ -14,18 +15,18 @@ IASSP2022 M2MeT挑战的侧重点是会议场景，它包括两个赛道：说 ## 时间安排(AOE时间) - $ 2023.4.29: $ 开放注册 -- $ 2023.5.8: $ 基线发布 -- $ 2023.5.15: $ 注册截止 -- $ 2023.6.9: $ 测试集数据发布 -- $ 2023.6.13: $ 最终结果提交截止 -- $ 2023.6.19: $ 评估结果和排名发布 -- $ 2023.7.3: $ 论文提交截止 -- $ 2023.7.10: $ 最终版论文提交截止 -- $ 2023.12.12: $ ASRU Workshop & challenge session +- $ 2023.5.11: $ 基线发布 +- $ 2023.5.22: $ 注册截止 +- $ 2023.6.16: $ 测试集数据发布，排行榜开放 +- $ 2023.6.20: $ 最终结果提交截止，排行榜关闭 +- $ 2023.6.26: $ 评估结果和排名发布 +- $ 2023.7.3: $ 论文提交截止（通过ASRU2023官方投稿，选择竞赛Session） +- $ 2023.7.10: $ 最终版论文提交截止（通过ASRU2023官方投稿，选择竞赛Session） +- $ 2023.12.12: $ ASRU Workshop & Challenge Session ## 竞赛报名 -来自学术界和工业界的有意向参赛者均应在2023年5月15日及之前填写下方的谷歌表单： +来自学术界和工业界的有意向参赛者均应在2023年5月22日及之前填写下方的谷歌表单。同时欢迎广大参赛者加入[官方交流微信群](https://alibaba-damo-academy.github.io/FunASR/m2met2_cn/%E8%81%94%E7%B3%BB%E6%96%B9%E5%BC%8F.html)交流并及时获取竞赛最新消息： [M2MET2.0报名](https://docs.google.com/forms/d/e/1FAIpQLSf77T9vAl7Ym-u5g8gXu18SBofoWRaFShBo26Ym0-HDxHW9PQ/viewform?usp=sf_link) diff --git a/docs/m2met2_cn/_build/html/genindex.html b/docs/m2met2_cn/_build/html/genindex.html index 5558bcf2f..1eee622f8 100644 --- a/docs/m2met2_cn/_build/html/genindex.html +++ b/docs/m2met2_cn/_build/html/genindex.html @@ -14,7 +14,7 @@ - 索引 — m2met2 文档 + 索引 — 多通道多方会议转录挑战2.0 @@ -36,7 +36,7 @@
  • 索引
    • -
  • m2met2 文档 »
    • +
  • 多通道多方会议转录挑战2.0 »
  • 索引
    • @@ -47,7 +47,7 @@
    + index.html" class="text-logo">多通道多方会议转录挑战2.0
    diff --git a/docs/m2met2_cn/_build/html/index.html b/docs/m2met2_cn/_build/html/index.html index fbc2fceac..5023d16a9 100644 --- a/docs/m2met2_cn/_build/html/index.html +++ b/docs/m2met2_cn/_build/html/index.html @@ -15,7 +15,7 @@ - ASRU 2023 多通道多方会议转录挑战 2.0 — m2met2 文档 + ASRU 2023 多通道多方会议转录挑战 2.0 — 多通道多方会议转录挑战2.0 @@ -41,7 +41,7 @@
  • 下一页 |
    • -
  • m2met2 文档 »
    • +
  • 多通道多方会议转录挑战2.0 »
  • ASRU 2023 多通道多方会议转录挑战 2.0
    • @@ -52,7 +52,7 @@
    + #" class="text-logo">多通道多方会议转录挑战2.0
    diff --git a/docs/m2met2_cn/_build/html/objects.inv b/docs/m2met2_cn/_build/html/objects.inv index 89341d391..d8466526b 100644 Binary files a/docs/m2met2_cn/_build/html/objects.inv and b/docs/m2met2_cn/_build/html/objects.inv differ diff --git a/docs/m2met2_cn/_build/html/search.html b/docs/m2met2_cn/_build/html/search.html index 4fe0684db..ca234a09b 100644 --- a/docs/m2met2_cn/_build/html/search.html +++ b/docs/m2met2_cn/_build/html/search.html @@ -14,7 +14,7 @@ - 搜索 — m2met2 文档 + 搜索 — 多通道多方会议转录挑战2.0 @@ -42,7 +42,7 @@
  • 索引
    • -
  • m2met2 文档 »
    • +
  • 多通道多方会议转录挑战2.0 »
  • 搜索
    • @@ -53,7 +53,7 @@
    + index.html" class="text-logo">多通道多方会议转录挑战2.0
    @@ -149,7 +149,7 @@
  • 索引
    • -
  • m2met2 文档 »
    • +
  • 多通道多方会议转录挑战2.0 »
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    • @@ -57,7 +57,7 @@
    + index.html" class="text-logo">多通道多方会议转录挑战2.0
    diff --git a/docs/m2met2_cn/conf.py b/docs/m2met2_cn/conf.py index da3a3327f..b6300d10d 100644 --- a/docs/m2met2_cn/conf.py +++ b/docs/m2met2_cn/conf.py @@ -7,7 +7,7 @@ import guzzle_sphinx_theme # -- Project information ----------------------------------------------------- # https://www.sphinx-doc.org/en/master/usage/configuration.html#project-information -project = 'm2met2' +project = '多通道多方会议转录挑战2.0' copyright = '2023, Speech Lab, Alibaba Group; ASLP Group, Northwestern Polytechnical University' author = 'Speech Lab, Alibaba Group; Audio, Speech and Language Processing Group, Northwestern Polytechnical University' diff --git a/docs/m2met2_cn/images/qrcode.png b/docs/m2met2_cn/images/qrcode.png index 68984beac..54b2f55d2 100644 Binary files a/docs/m2met2_cn/images/qrcode.png and b/docs/m2met2_cn/images/qrcode.png differ diff --git a/docs/m2met2_cn/基线.md b/docs/m2met2_cn/基线.md index e4d02f72e..4b031beee 100644 --- a/docs/m2met2_cn/基线.md +++ b/docs/m2met2_cn/基线.md @@ -5,8 +5,27 @@ ![model archietecture](images/sa_asr_arch.png) ## 快速开始 -#TODO: fill with the README.md of the baseline - +首先需要安装FunASR和ModelScope. ([installation](https://alibaba-damo-academy.github.io/FunASR/en/installation.html)) +基线系统有训练和测试两个脚本，`run.sh` 是用于训练基线系统并在M2MET的验证与测试集上评估的，而 `run_m2met_2023_infer.sh` 用于此次竞赛预备开放的全新测试集上测试同时生成符合竞赛最终提交格式的文件。 +在运行 `run.sh`前，需要自行下载并解压[AliMeeting](http://www.openslr.org/119/)数据集并放置于`./dataset`目录下： +```shell +dataset +|—— Eval_Ali_far +|—— Eval_Ali_near +|—— Test_Ali_far +|—— Test_Ali_near +|—— Train_Ali_far +|—— Train_Ali_near +在运行 `run_m2met_2023_infer.sh`前, 需要将测试集`Test_2023_Ali_far`（仅包含音频，将于6.16发布）放置于`./dataset`目录下。然后将主办方提供的`wav.scp`，`wav_raw.scp`，`segments`，`utt2spk`和`spk2utt`放置于`./data/Test_2023_Ali_far`目录下。 +```shell +data/Test_2023_Ali_far +|—— wav.scp +|—— wav_raw.scp +|—— segments +|—— utt2spk +|—— spk2utt +``` +更多基线系统详情见[此处](https://github.com/alibaba-damo-academy/FunASR/blob/main/egs/alimeeting/sa-asr/README.md) ## 基线结果 基线系统的结果如表3所示。在训练期间，说话人档案采用了真实说话人嵌入。然而由于在评估过程中缺乏真实说话人标签，因此使用了由额外的谱聚类提供的说话人特征。同时我们还提供了在评估和测试集上使用真实说话人档案的结果，以显示说话人档案准确性的影响。 ![baseline result](images/baseline_result.png) \ No newline at end of file diff --git a/docs/m2met2_cn/简介.md b/docs/m2met2_cn/简介.md index 5afb6a099..7f2925bf3 100644 --- a/docs/m2met2_cn/简介.md +++ b/docs/m2met2_cn/简介.md @@ -1,5 +1,6 @@ # 简介 ## 竞赛介绍 + 语音识别（Automatic Speech Recognition）、说话人日志（Speaker Diarization）等语音处理技术的最新发展激发了众多智能语音的广泛应用。然而会议场景由于其复杂的声学条件和不同的讲话风格，包括重叠的讲话、不同数量的发言者、大会议室的远场信号以及环境噪声和混响，仍然属于一项极具挑战性的任务。 为了推动会议场景语音识别的发展，已经有很多相关的挑战赛，如 Rich Transcription evaluation 和 CHIME（Computational Hearing in Multisource Environments） 挑战赛。最新的CHIME挑战赛关注于远距离自动语音识别和开发能在各种不同拓扑结构的阵列和应用场景中通用的系统。然而不同语言之间的差异限制了非英语会议转录的进展。MISP（Multimodal Information Based Speech Processing）和M2MeT（Multi-Channel Multi-Party Meeting Transcription）挑战赛为推动普通话会议场景语音识别做出了贡献。MISP挑战赛侧重于用视听多模态的方法解决日常家庭环境中的远距离多麦克风信号处理问题，而M2MeT挑战则侧重于解决离线会议室中会议转录的语音重叠问题。 @@ -14,18 +15,18 @@ IASSP2022 M2MeT挑战的侧重点是会议场景，它包括两个赛道：说 ## 时间安排(AOE时间) - $ 2023.4.29: $ 开放注册 -- $ 2023.5.8: $ 基线发布 -- $ 2023.5.15: $ 注册截止 -- $ 2023.6.9: $ 测试集数据发布 -- $ 2023.6.13: $ 最终结果提交截止 -- $ 2023.6.19: $ 评估结果和排名发布 -- $ 2023.7.3: $ 论文提交截止 -- $ 2023.7.10: $ 最终版论文提交截止 -- $ 2023.12.12: $ ASRU Workshop & challenge session +- $ 2023.5.11: $ 基线发布 +- $ 2023.5.22: $ 注册截止 +- $ 2023.6.16: $ 测试集数据发布，排行榜开放 +- $ 2023.6.20: $ 最终结果提交截止，排行榜关闭 +- $ 2023.6.26: $ 评估结果和排名发布 +- $ 2023.7.3: $ 论文提交截止（通过ASRU2023官方投稿，选择竞赛Session） +- $ 2023.7.10: $ 最终版论文提交截止（通过ASRU2023官方投稿，选择竞赛Session） +- $ 2023.12.12: $ ASRU Workshop & Challenge Session ## 竞赛报名 -来自学术界和工业界的有意向参赛者均应在2023年5月15日及之前填写下方的谷歌表单： +来自学术界和工业界的有意向参赛者均应在2023年5月22日及之前填写下方的谷歌表单。同时欢迎广大参赛者加入[官方交流微信群](https://alibaba-damo-academy.github.io/FunASR/m2met2_cn/%E8%81%94%E7%B3%BB%E6%96%B9%E5%BC%8F.html)交流并及时获取竞赛最新消息： [M2MET2.0报名](https://docs.google.com/forms/d/e/1FAIpQLSf77T9vAl7Ym-u5g8gXu18SBofoWRaFShBo26Ym0-HDxHW9PQ/viewform?usp=sf_link)