From 48ee4dd536242f25bb157c7962941c3661b4286b Mon Sep 17 00:00:00 2001
From: yhliang <429259365@qq.com>
Date: 星期三, 10 五月 2023 17:12:30 +0800
Subject: [PATCH] fix format error

---
 docs/m2met2/_build/html/Introduction.html            |    2 +-
 docs/m2met2_cn/_build/doctrees/简介.doctree            |    0 
 docs/m2met2/_build/html/_sources/Introduction.md.txt |    2 +-
 docs/m2met2_cn/_build/doctrees/联系方式.doctree          |    0 
 docs/m2met2/_build/doctrees/environment.pickle       |    0 
 docs/m2met2_cn/_build/doctrees/赛道设置与评估.doctree       |    0 
 docs/m2met2_cn/_build/html/searchindex.js            |    2 +-
 docs/m2met2/_build/doctrees/Contact.doctree          |    0 
 docs/m2met2/_build/html/_sources/Baseline.md.txt     |    1 +
 docs/m2met2_cn/_build/html/简介.html                   |    2 +-
 docs/m2met2/_build/html/Baseline.html                |    7 ++++---
 docs/m2met2_cn/_build/doctrees/index.doctree         |    0 
 docs/m2met2/_build/doctrees/Baseline.doctree         |    0 
 docs/m2met2_cn/_build/html/基线.html                   |    9 +++++----
 docs/m2met2/_build/html/searchindex.js               |    2 +-
 docs/m2met2_cn/_build/html/_sources/基线.md.txt        |    5 +++--
 docs/m2met2_cn/_build/doctrees/environment.pickle    |    0 
 docs/m2met2_cn/_build/doctrees/基线.doctree            |    0 
 docs/m2met2/_build/doctrees/Introduction.doctree     |    0 
 docs/m2met2_cn/_build/html/_sources/简介.md.txt        |    2 +-
 20 files changed, 19 insertions(+), 15 deletions(-)

diff --git a/docs/m2met2/_build/doctrees/Baseline.doctree b/docs/m2met2/_build/doctrees/Baseline.doctree
index b257764..a99a9af 100644
--- a/docs/m2met2/_build/doctrees/Baseline.doctree
+++ b/docs/m2met2/_build/doctrees/Baseline.doctree
Binary files differ
diff --git a/docs/m2met2/_build/doctrees/Contact.doctree b/docs/m2met2/_build/doctrees/Contact.doctree
index 877cb68..0508819 100644
--- a/docs/m2met2/_build/doctrees/Contact.doctree
+++ b/docs/m2met2/_build/doctrees/Contact.doctree
Binary files differ
diff --git a/docs/m2met2/_build/doctrees/Introduction.doctree b/docs/m2met2/_build/doctrees/Introduction.doctree
index b3a25f1..96e4276 100644
--- a/docs/m2met2/_build/doctrees/Introduction.doctree
+++ b/docs/m2met2/_build/doctrees/Introduction.doctree
Binary files differ
diff --git a/docs/m2met2/_build/doctrees/environment.pickle b/docs/m2met2/_build/doctrees/environment.pickle
index 6abb448..aae3d36 100644
--- a/docs/m2met2/_build/doctrees/environment.pickle
+++ b/docs/m2met2/_build/doctrees/environment.pickle
Binary files differ
diff --git a/docs/m2met2/_build/html/Baseline.html b/docs/m2met2/_build/html/Baseline.html
index 3db1438..7fef329 100644
--- a/docs/m2met2/_build/html/Baseline.html
+++ b/docs/m2met2/_build/html/Baseline.html
@@ -141,9 +141,10 @@
 <span class="p">|</span>鈥斺��<span class="w"> </span>Test_Ali_near
 <span class="p">|</span>鈥斺��<span class="w"> </span>Train_Ali_far
 <span class="p">|</span>鈥斺��<span class="w"> </span>Train_Ali_near
-Before<span class="w"> </span>running<span class="w"> </span><span class="sb">`</span>run_m2met_2023_infer.sh<span class="sb">`</span>,<span class="w"> </span>you<span class="w"> </span>need<span class="w"> </span>to<span class="w"> </span>place<span class="w"> </span>the<span class="w"> </span>new<span class="w"> </span><span class="nb">test</span><span class="w"> </span><span class="nb">set</span><span class="w"> </span><span class="sb">`</span>Test_2023_Ali_far<span class="sb">`</span><span class="w"> </span><span class="o">(</span>to<span class="w"> </span>be<span class="w"> </span>released<span class="w"> </span>after<span class="w"> </span>the<span class="w"> </span>challenge<span class="w"> </span>starts<span class="o">)</span><span class="w"> </span><span class="k">in</span><span class="w"> </span>the<span class="w"> </span><span class="sb">`</span>./dataset<span class="sb">`</span><span class="w"> </span>directory,<span class="w"> </span>which<span class="w"> </span>contains<span class="w"> </span>only<span class="w"> </span>raw<span class="w"> </span>audios.<span class="w"> </span>Then<span class="w"> </span>put<span class="w"> </span>the<span class="w"> </span>given<span class="w"> </span><span class="sb">`</span>wav.scp<span class="sb">`</span>,<span class="w"> </span><span class="sb">`</span>wav_raw.scp<span class="sb">`</span>,<span class="w"> </span><span class="sb">`</span>segments<span class="sb">`</span>,<span class="w"> </span><span class="sb">`</span>utt2spk<span class="sb">`</span><span class="w"> </span>and<span class="w"> </span><span class="sb">`</span>spk2utt<span class="sb">`</span><span class="w"> </span><span class="k">in</span><span class="w"> </span>the<span class="w"> </span><span class="sb">`</span>./data/Test_2023_Ali_far<span class="sb">`</span><span class="w"> </span>directory.<span class="w">  </span>
-<span class="sb">```</span>shell
-data/Test_2023_Ali_far
+</pre></div>
+</div>
+<p>Before running <code class="docutils literal notranslate"><span class="pre">run_m2met_2023_infer.sh</span></code>, you need to place the new test set <code class="docutils literal notranslate"><span class="pre">Test_2023_Ali_far</span></code> (to be released after the challenge starts) in the <code class="docutils literal notranslate"><span class="pre">./dataset</span></code> directory, which contains only raw audios. Then put the given <code class="docutils literal notranslate"><span class="pre">wav.scp</span></code>, <code class="docutils literal notranslate"><span class="pre">wav_raw.scp</span></code>, <code class="docutils literal notranslate"><span class="pre">segments</span></code>, <code class="docutils literal notranslate"><span class="pre">utt2spk</span></code> and <code class="docutils literal notranslate"><span class="pre">spk2utt</span></code> in the <code class="docutils literal notranslate"><span class="pre">./data/Test_2023_Ali_far</span></code> directory.</p>
+<div class="highlight-shell notranslate"><div class="highlight"><pre><span></span>data/Test_2023_Ali_far
 <span class="p">|</span>鈥斺��<span class="w"> </span>wav.scp
 <span class="p">|</span>鈥斺��<span class="w"> </span>wav_raw.scp
 <span class="p">|</span>鈥斺��<span class="w"> </span>segments
diff --git a/docs/m2met2/_build/html/Introduction.html b/docs/m2met2/_build/html/Introduction.html
index 45ea2dc..b3079bd 100644
--- a/docs/m2met2/_build/html/Introduction.html
+++ b/docs/m2met2/_build/html/Introduction.html
@@ -130,7 +130,7 @@
 <p>Automatic speech recognition (ASR) and speaker diarization have made significant strides in recent years, resulting in a surge of speech technology applications across various domains. However, meetings present unique challenges to speech technologies due to their complex acoustic conditions and diverse speaking styles, including overlapping speech, variable numbers of speakers, far-field signals in large conference rooms, and environmental noise and reverberation.</p>
 <p>Over the years, several challenges have been organized to advance the development of meeting transcription, including the Rich Transcription evaluation and Computational Hearing in Multisource Environments (CHIME) challenges. The latest iteration of the CHIME challenge has a particular focus on distant automatic speech recognition and developing systems that can generalize across various array topologies and application scenarios. However, while progress has been made in English meeting transcription, language differences remain a significant barrier to achieving comparable results in non-English languages, such as Mandarin. The Multimodal Information Based Speech Processing (MISP) and Multi-Channel Multi-Party Meeting Transcription (M2MeT) challenges have been instrumental in advancing Mandarin meeting transcription. The MISP challenge seeks to address the problem of audio-visual distant multi-microphone signal processing in everyday home environments, while the M2MeT challenge focuses on tackling the speech overlap issue in offline meeting rooms.</p>
 <p>The ICASSP2022 M2MeT challenge focuses on meeting scenarios, and it comprises two main tasks: speaker diarization and multi-speaker automatic speech recognition. The former involves identifying who spoke when in the meeting, while the latter aims to transcribe speech from multiple speakers simultaneously, which poses significant technical difficulties due to overlapping speech and acoustic interferences.</p>
-<p>Building on the success of the previous M2MeT challenge, we are excited to propose the M2MeT2.0 challenge as an ASRU2023 challenge special session. In the original M2MeT challenge, the evaluation metric was speaker-independent, which meant that the transcription could be determined, but not the corresponding speaker. To address this limitation and further advance the current multi-talker ASR system towards practicality, the M2MeT2.0 challenge proposes the speaker-attributed ASR task with two sub-tracks: fixed and open training conditions. The speaker-attribute automatic speech recognition (ASR) task aims to tackle the practical and challenging problem of identifying 鈥渨ho spoke what at when鈥�. To facilitate reproducible research in this field, we offer a comprehensive overview of the dataset, rules, evaluation metrics, and baseline systems. Furthermore, we will release a carefully curated test set, comprising approximately 10 hours of audio, according to the timeline. The new test set is designed to enable researchers to validate and compare their models鈥� performance and advance the state of the art in this area.</p>
+<p>Building on the success of the previous M2MeT challenge, we are excited to propose the M2MeT2.0 challenge as an ASRU 2023 challenge special session. In the original M2MeT challenge, the evaluation metric was speaker-independent, which meant that the transcription could be determined, but not the corresponding speaker. To address this limitation and further advance the current multi-talker ASR system towards practicality, the M2MeT2.0 challenge proposes the speaker-attributed ASR task with two sub-tracks: fixed and open training conditions. The speaker-attribute automatic speech recognition (ASR) task aims to tackle the practical and challenging problem of identifying 鈥渨ho spoke what at when鈥�. To facilitate reproducible research in this field, we offer a comprehensive overview of the dataset, rules, evaluation metrics, and baseline systems. Furthermore, we will release a carefully curated test set, comprising approximately 10 hours of audio, according to the timeline. The new test set is designed to enable researchers to validate and compare their models鈥� performance and advance the state of the art in this area.</p>
 </section>
 <section id="timeline-aoe-time">
 <h2>Timeline(AOE Time)<a class="headerlink" href="#timeline-aoe-time" title="Permalink to this heading">露</a></h2>
diff --git a/docs/m2met2/_build/html/_sources/Baseline.md.txt b/docs/m2met2/_build/html/_sources/Baseline.md.txt
index 728a375..cdaff8a 100644
--- a/docs/m2met2/_build/html/_sources/Baseline.md.txt
+++ b/docs/m2met2/_build/html/_sources/Baseline.md.txt
@@ -16,6 +16,7 @@
 |鈥斺�� Test_Ali_near
 |鈥斺�� Train_Ali_far
 |鈥斺�� 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
diff --git a/docs/m2met2/_build/html/_sources/Introduction.md.txt b/docs/m2met2/_build/html/_sources/Introduction.md.txt
index 7107bf5..06c27b2 100644
--- a/docs/m2met2/_build/html/_sources/Introduction.md.txt
+++ b/docs/m2met2/_build/html/_sources/Introduction.md.txt
@@ -6,7 +6,7 @@
 
 The ICASSP2022 M2MeT challenge focuses on meeting scenarios, and it comprises two main tasks: speaker diarization and multi-speaker automatic speech recognition. The former involves identifying who spoke when in the meeting, while the latter aims to transcribe speech from multiple speakers simultaneously, which poses significant technical difficulties due to overlapping speech and acoustic interferences.
 
-Building on the success of the previous M2MeT challenge, we are excited to propose the M2MeT2.0 challenge as an ASRU2023 challenge special session. In the original M2MeT challenge, the evaluation metric was speaker-independent, which meant that the transcription could be determined, but not the corresponding speaker. To address this limitation and further advance the current multi-talker ASR system towards practicality, the M2MeT2.0 challenge proposes the speaker-attributed ASR task with two sub-tracks: fixed and open training conditions. The speaker-attribute automatic speech recognition (ASR) task aims to tackle the practical and challenging problem of identifying "who spoke what at when". To facilitate reproducible research in this field, we offer a comprehensive overview of the dataset, rules, evaluation metrics, and baseline systems. Furthermore, we will release a carefully curated test set, comprising approximately 10 hours of audio, according to the timeline. The new test set is designed to enable researchers to validate and compare their models' performance and advance the state of the art in this area.
+Building on the success of the previous M2MeT challenge, we are excited to propose the M2MeT2.0 challenge as an ASRU 2023 challenge special session. In the original M2MeT challenge, the evaluation metric was speaker-independent, which meant that the transcription could be determined, but not the corresponding speaker. To address this limitation and further advance the current multi-talker ASR system towards practicality, the M2MeT2.0 challenge proposes the speaker-attributed ASR task with two sub-tracks: fixed and open training conditions. The speaker-attribute automatic speech recognition (ASR) task aims to tackle the practical and challenging problem of identifying "who spoke what at when". To facilitate reproducible research in this field, we offer a comprehensive overview of the dataset, rules, evaluation metrics, and baseline systems. Furthermore, we will release a carefully curated test set, comprising approximately 10 hours of audio, according to the timeline. The new test set is designed to enable researchers to validate and compare their models' performance and advance the state of the art in this area.
 
 ## Timeline(AOE Time)
 - $ April~29, 2023: $ Challenge and registration open.
diff --git a/docs/m2met2/_build/html/searchindex.js b/docs/m2met2/_build/html/searchindex.js
index 9f44199..6481ef2 100644
--- a/docs/m2met2/_build/html/searchindex.js
+++ b/docs/m2met2/_build/html/searchindex.js
@@ -1 +1 @@
-Search.setIndex({"docnames": ["Baseline", "Contact", "Dataset", "Introduction", "Organizers", "Rules", "Track_setting_and_evaluation", "index"], "filenames": ["Baseline.md", "Contact.md", "Dataset.md", "Introduction.md", "Organizers.md", "Rules.md", "Track_setting_and_evaluation.md", "index.rst"], "titles": ["Baseline", "Contact", "Datasets", "Introduction", "Organizers", "Rules", "Track &amp; Evaluation", "ASRU 2023 MULTI-CHANNEL MULTI-PARTY MEETING TRANSCRIPTION CHALLENGE 2.0 (M2MeT2.0)"], "terms": {"we": [0, 2, 3, 7], "releas": [0, 2, 3, 6], "an": [0, 2, 3, 6], "e2": 0, "sa": 0, "asr": [0, 3, 7], "conduct": [0, 2], "funasr": 0, "time": [0, 6], "accord": [0, 3], "timelin": [0, 2], "The": [0, 2, 3, 5, 6], "model": [0, 2, 3, 5, 6], "architectur": 0, "i": [0, 2, 3, 5], "shown": [0, 2], "figur": [0, 6], "3": [0, 2, 3], "speakerencod": 0, "initi": 0, "pre": [0, 6], "train": [0, 3, 5, 7], "speaker": [0, 2, 3, 7], "verif": 0, "from": [0, 2, 3, 5, 6], "modelscop": [0, 6], "thi": [0, 3, 5, 6], "also": [0, 2, 3, 6], "us": [0, 2, 5, 6], "extract": 0, "embed": 0, "profil": 0, "To": [0, 2, 3, 7], "run": 0, "first": 0, "you": [0, 1], "need": 0, "instal": 0, "There": [0, 2], "ar": [0, 2, 3, 5, 6, 7], "two": [0, 3, 5, 7], "startup": 0, "script": [0, 2], "sh": 0, "evalu": [0, 2, 3, 7], "old": 0, "eval": [0, 2, 5, 6], "test": [0, 2, 3, 5, 6], "set": [0, 2, 3, 5, 6], "run_m2met_2023_inf": 0, "infer": 0, "new": [0, 2, 3, 6], "multi": [0, 3, 6], "channel": [0, 3], "parti": [0, 3, 6], "meet": [0, 2, 3, 6], "transcript": [0, 2, 3, 5, 6], "2": [0, 2, 6], "0": [0, 1, 2, 3], "m2met2": [0, 1, 3], "challeng": [0, 1, 3, 5, 6], "befor": 0, "must": [0, 3, 5, 6], "manual": [0, 6], "download": [0, 2], "unpack": 0, "alimeet": [0, 1, 6], "corpu": [0, 6], "place": [0, 2], "dataset": [0, 3, 5, 6, 7], "directori": 0, "eval_ali_far": 0, "eval_ali_near": 0, "test_ali_far": 0, "test_ali_near": 0, "train_ali_far": 0, "train_ali_near": 0, "test_2023_ali_far": 0, "after": 0, "which": [0, 2, 3, 6], "contain": [0, 2, 6], "onli": [0, 2, 5, 6], "raw": 0, "audio": [0, 2, 3, 6], "Then": 0, "put": 0, "given": 0, "wav": 0, "scp": 0, "wav_raw": 0, "segment": [0, 2, 6], "utt2spk": 0, "spk2utt": 0, "data": [0, 3, 5, 6], "shell": 0, "For": [0, 2], "more": [0, 2], "detail": [0, 3, 6], "can": [0, 2, 3, 5, 6], "see": 0, "here": 0, "system": [0, 3, 5, 6, 7], "tabl": [0, 2], "adopt": 0, "oracl": [0, 6], "dure": [0, 2, 6], "howev": [0, 3, 6], "due": [0, 3], "lack": 0, "label": [0, 5, 6], "provid": [0, 2, 6, 7], "addit": [0, 6], "spectral": 0, "cluster": 0, "meanwhil": 0, "show": 0, "impact": 0, "accuraci": [0, 6], "If": [1, 5, 6], "have": [1, 3], "ani": [1, 5, 6], "question": 1, "about": [1, 3], "pleas": 1, "u": [1, 2], "email": [1, 3, 4], "m2met": [1, 3, 6, 7], "gmail": 1, "com": [1, 4], "wechat": [1, 3], "group": [1, 2, 3], "In": [2, 3, 5], "fix": [2, 3, 7], "condit": [2, 3, 7], "restrict": 2, "three": [2, 3, 6], "publicli": [2, 6], "avail": [2, 6], "corpora": 2, "name": 2, "aishel": [2, 4, 6], "4": [2, 6], "cn": [2, 4, 6], "celeb": [2, 6], "perform": [2, 3], "call": 2, "2023": [2, 3, 5, 6], "score": [2, 6], "rank": [2, 3, 6], "describ": 2, "118": 2, "75": 2, "hour": [2, 3, 6], "speech": [2, 3, 6, 7], "total": [2, 6], "divid": [2, 6], "104": 2, "10": [2, 3, 6], "specif": [2, 6], "212": 2, "8": [2, 3], "20": 2, "session": [2, 3, 6, 7], "respect": 2, "each": [2, 3, 6], "consist": [2, 6], "15": [2, 3], "30": 2, "minut": 2, "discuss": 2, "particip": [2, 5, 6], "number": [2, 3, 6], "456": 2, "25": 2, "60": 2, "balanc": 2, "gender": 2, "coverag": 2, "collect": 2, "13": [2, 3], "venu": 2, "categor": 2, "type": 2, "small": 2, "medium": 2, "larg": [2, 3], "room": [2, 3], "size": 2, "rang": 2, "m": 2, "55": 2, "differ": [2, 3, 6], "give": 2, "varieti": 2, "acoust": [2, 3, 6], "properti": 2, "layout": 2, "paramet": [2, 5], "togeth": 2, "wall": 2, "materi": 2, "cover": 2, "cement": 2, "glass": 2, "etc": 2, "other": 2, "furnish": 2, "includ": [2, 3, 5, 6], "sofa": 2, "tv": 2, 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{"baselin": 0, "overview": [0, 2], "quick": 0, "start": 0, "result": 0, "contact": 1, "dataset": 2, "train": [2, 6], "data": 2, "detail": 2, "alimeet": 2, "corpu": 2, "get": 2, "introduct": 3, "call": 3, "particip": 3, "timelin": 3, "aoe": 3, "time": 3, "guidelin": 3, "organ": 4, "rule": 5, "track": 6, "evalu": 6, "speaker": 6, "attribut": 6, "asr": 6, "metric": 6, "sub": 6, "arrang": 6, "i": 6, "fix": 6, "condit": 6, "ii": 6, "open": 6, "asru": 7, "2023": 7, "multi": 7, "channel": 7, "parti": 7, "meet": 7, "transcript": 7, "challeng": 7, "2": 7, "0": 7, "m2met2": 7, "content": 7}, "envversion": {"sphinx.domains.c": 2, "sphinx.domains.changeset": 1, "sphinx.domains.citation": 1, "sphinx.domains.cpp": 8, "sphinx.domains.index": 1, "sphinx.domains.javascript": 2, "sphinx.domains.math": 2, "sphinx.domains.python": 3, "sphinx.domains.rst": 2, "sphinx.domains.std": 2, "sphinx": 57}, "alltitles": {"Baseline": [[0, "baseline"]], "Overview": [[0, "overview"]], "Quick start": [[0, "quick-start"]], "Baseline results": [[0, "baseline-results"]], "Contact": [[1, "contact"]], "Datasets": [[2, "datasets"]], "Overview of training data": [[2, "overview-of-training-data"]], "Detail of AliMeeting corpus": [[2, "detail-of-alimeeting-corpus"]], "Get the data": [[2, "get-the-data"]], "Introduction": [[3, "introduction"]], "Call for participation": [[3, "call-for-participation"]], "Timeline(AOE Time)": [[3, "timeline-aoe-time"]], "Guidelines": [[3, "guidelines"]], "Organizers": [[4, "organizers"]], "Rules": [[5, "rules"]], "Track & Evaluation": [[6, "track-evaluation"]], "Speaker-Attributed ASR": [[6, "speaker-attributed-asr"]], "Evaluation metric": [[6, "evaluation-metric"]], "Sub-track arrangement": [[6, "sub-track-arrangement"]], "Sub-track I (Fixed Training Condition):": [[6, "sub-track-i-fixed-training-condition"]], "Sub-track II (Open Training Condition):": [[6, "sub-track-ii-open-training-condition"]], "ASRU 2023 MULTI-CHANNEL MULTI-PARTY MEETING TRANSCRIPTION CHALLENGE 2.0 (M2MeT2.0)": [[7, "asru-2023-multi-channel-multi-party-meeting-transcription-challenge-2-0-m2met2-0"]], "Contents:": [[7, null]]}, "indexentries": {}})
\ No newline at end of file
diff --git a/docs/m2met2_cn/_build/doctrees/environment.pickle b/docs/m2met2_cn/_build/doctrees/environment.pickle
index e3a184d..178fe18 100644
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index 77742ac..1677b8b 100644
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diff --git "a/docs/m2met2_cn/_build/doctrees/\345\237\272\347\272\277.doctree" "b/docs/m2met2_cn/_build/doctrees/\345\237\272\347\272\277.doctree"
index f33c2e1..9215986 100644
--- "a/docs/m2met2_cn/_build/doctrees/\345\237\272\347\272\277.doctree"
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index b7f635a..595b41e 100644
--- "a/docs/m2met2_cn/_build/doctrees/\347\256\200\344\273\213.doctree"
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index e7e7889..6b8208a 100644
--- "a/docs/m2met2_cn/_build/doctrees/\350\201\224\347\263\273\346\226\271\345\274\217.doctree"
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index fa83a0c..c6be4ae 100644
--- "a/docs/m2met2_cn/_build/doctrees/\350\265\233\351\201\223\350\256\276\347\275\256\344\270\216\350\257\204\344\274\260.doctree"
+++ "b/docs/m2met2_cn/_build/doctrees/\350\265\233\351\201\223\350\256\276\347\275\256\344\270\216\350\257\204\344\274\260.doctree"
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diff --git "a/docs/m2met2_cn/_build/html/_sources/\345\237\272\347\272\277.md.txt" "b/docs/m2met2_cn/_build/html/_sources/\345\237\272\347\272\277.md.txt"
index ddf8275..fab780b 100644
--- "a/docs/m2met2_cn/_build/html/_sources/\345\237\272\347\272\277.md.txt"
+++ "b/docs/m2met2_cn/_build/html/_sources/\345\237\272\347\272\277.md.txt"
@@ -6,7 +6,7 @@
 
 ## 蹇�熷紑濮�
 棣栧厛闇�瑕佸畨瑁匜unASR鍜孧odelScope. ([installation](https://alibaba-damo-academy.github.io/FunASR/en/installation.html))  
-鍩虹嚎绯荤粺鏈夎缁冨拰娴嬭瘯涓や釜鑴氭湰锛宍run.sh` 鏄敤浜庤缁冨熀绾跨郴缁熷苟鍦∕2MeT鐨勯獙璇佷笌娴嬭瘯闆嗕笂璇勪及鐨勶紝鑰� `run_m2met_2023_infer.sh` 鐢ㄤ簬姝ゆ绔炶禌棰勫寮�鏀剧殑鍏ㄦ柊娴嬭瘯闆嗕笂娴嬭瘯鍚屾椂鐢熸垚绗﹀悎绔炶禌鏈�缁堟彁浜ゆ牸寮忕殑鏂囦欢銆�
+鍩虹嚎绯荤粺鏈夎缁冨拰娴嬭瘯涓や釜鑴氭湰,`run.sh`鏄敤浜庤缁冨熀绾跨郴缁熷苟鍦∕2MeT鐨勯獙璇佷笌娴嬭瘯闆嗕笂璇勪及鐨勶紝鑰宍run_m2met_2023_infer.sh`鐢ㄤ簬姝ゆ绔炶禌棰勫寮�鏀剧殑鍏ㄦ柊娴嬭瘯闆嗕笂娴嬭瘯鍚屾椂鐢熸垚绗﹀悎绔炶禌鏈�缁堟彁浜ゆ牸寮忕殑鏂囦欢銆�
 鍦ㄨ繍琛� `run.sh`鍓嶏紝闇�瑕佽嚜琛屼笅杞藉苟瑙ｅ帇[AliMeeting](http://www.openslr.org/119/)鏁版嵁闆嗗苟鏀剧疆浜巂./dataset`鐩綍涓嬶細
 ```shell
 dataset
@@ -16,7 +16,8 @@
 |鈥斺�� Test_Ali_near
 |鈥斺�� Train_Ali_far
 |鈥斺�� Train_Ali_near
-鍦ㄨ繍琛� `run_m2met_2023_infer.sh`鍓�, 闇�瑕佸皢娴嬭瘯闆哷Test_2023_Ali_far`锛堜粎鍖呭惈闊抽锛屽皢浜�6.16鍙戝竷锛夋斁缃簬`./dataset`鐩綍涓嬨�傜劧鍚庡皢涓诲姙鏂规彁渚涚殑`wav.scp`锛宍wav_raw.scp`锛宍segments`锛宍utt2spk`鍜宍spk2utt`鏀剧疆浜巂./data/Test_2023_Ali_far`鐩綍涓嬨��
+```
+鍦ㄨ繍琛宍run_m2met_2023_infer.sh`鍓�, 闇�瑕佸皢娴嬭瘯闆哷Test_2023_Ali_far`锛堜粎鍖呭惈闊抽锛屽皢浜�6.16鍙戝竷锛夋斁缃簬`./dataset`鐩綍涓嬨�傜劧鍚庡皢涓诲姙鏂规彁渚涚殑`wav.scp`锛宍wav_raw.scp`锛宍segments`锛宍utt2spk`鍜宍spk2utt`鏀剧疆浜巂./data/Test_2023_Ali_far`鐩綍涓嬨��
 ```shell
 data/Test_2023_Ali_far
 |鈥斺�� wav.scp
diff --git "a/docs/m2met2_cn/_build/html/_sources/\347\256\200\344\273\213.md.txt" "b/docs/m2met2_cn/_build/html/_sources/\347\256\200\344\273\213.md.txt"
index 1e23e11..be456ff 100644
--- "a/docs/m2met2_cn/_build/html/_sources/\347\256\200\344\273\213.md.txt"
+++ "b/docs/m2met2_cn/_build/html/_sources/\347\256\200\344\273\213.md.txt"
@@ -7,7 +7,7 @@
 
 IASSP2022 M2MeT鎸戞垬鐨勪晶閲嶇偣鏄細璁満鏅紝瀹冨寘鎷袱涓禌閬擄細璇磋瘽浜烘棩璁板拰澶氳璇濅汉鑷姩璇煶璇嗗埆銆傚墠鑰呮秹鍙婅瘑鍒�滆皝鍦ㄤ粈涔堟椂鍊欒浜嗚瘽鈥濓紝鑰屽悗鑰呮棬鍦ㄥ悓鏃惰瘑鍒潵鑷涓璇濅汉鐨勮闊筹紝璇煶閲嶅彔鍜屽悇绉嶅櫔澹板甫鏉ヤ簡宸ㄥぇ鐨勬妧鏈洶闅俱��
 
-鍦ㄤ笂涓�灞奙2MeT鎴愬姛涓惧姙鐨勫熀纭�涓婏紝鎴戜滑灏嗗湪ASRU2023涓婄户缁妇鍔濵2MeT2.0鎸戞垬璧涖�傚湪涓婁竴灞奙2MeT鎸戞垬璧涗腑锛岃瘎浼版寚鏍囨槸璇磋瘽浜烘棤鍏崇殑锛屾垜浠彧鑳藉緱鍒拌瘑鍒枃鏈紝鑰屼笉鑳界‘瀹氱浉搴旂殑璇磋瘽浜恒��
+鍦ㄤ笂涓�灞奙2MeT鎴愬姛涓惧姙鐨勫熀纭�涓婏紝鎴戜滑灏嗗湪ASRU 2023涓婄户缁妇鍔濵2MeT2.0鎸戞垬璧涖�傚湪涓婁竴灞奙2MeT鎸戞垬璧涗腑锛岃瘎浼版寚鏍囨槸璇磋瘽浜烘棤鍏崇殑锛屾垜浠彧鑳藉緱鍒拌瘑鍒枃鏈紝鑰屼笉鑳界‘瀹氱浉搴旂殑璇磋瘽浜恒��
 涓轰簡瑙ｅ喅杩欎竴灞�闄愭�у苟灏嗙幇鍦ㄧ殑澶氳璇濅汉璇煶璇嗗埆绯荤粺鎺ㄥ悜瀹炵敤鍖栵紝M2MeT2.0鎸戞垬璧涘皢鍦ㄨ璇濅汉鐩稿叧鐨勪汉鐗╀笂璇勪及锛屽苟涓斿悓鏃惰绔嬮檺瀹氭暟鎹笌涓嶉檺瀹氭暟鎹袱涓瓙璧涢亾銆傞�氳繃灏嗚闊冲綊灞炰簬鐗瑰畾鐨勮璇濅汉锛岃繖椤逛换鍔℃棬鍦ㄦ彁楂樺璇磋瘽浜篈SR绯荤粺鍦ㄧ湡瀹炰笘鐣岀幆澧冧腑鐨勫噯纭�у拰閫傜敤鎬с��
 鎴戜滑瀵规暟鎹泦銆佽鍒欍�佸熀绾跨郴缁熷拰璇勪及鏂规硶杩涜浜嗚缁嗕粙缁嶏紝浠ヨ繘涓�姝ヤ績杩涘璇磋瘽浜鸿闊宠瘑鍒鍩熺爺绌剁殑鍙戝睍銆傛澶栵紝鎴戜滑灏嗘牴鎹椂闂磋〃鍙戝竷涓�涓叏鏂扮殑娴嬭瘯闆嗭紝鍖呮嫭澶х害10灏忔椂鐨勯煶棰戙��
 
diff --git a/docs/m2met2_cn/_build/html/searchindex.js b/docs/m2met2_cn/_build/html/searchindex.js
index a368095..2e211ff 100644
--- a/docs/m2met2_cn/_build/html/searchindex.js
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@@ -1 +1 @@
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diff --git "a/docs/m2met2_cn/_build/html/\345\237\272\347\272\277.html" "b/docs/m2met2_cn/_build/html/\345\237\272\347\272\277.html"
index 16e215f..7bfec93 100644
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+++ "b/docs/m2met2_cn/_build/html/\345\237\272\347\272\277.html"
@@ -133,7 +133,7 @@
 <section id="id3">
 <h2>蹇�熷紑濮�<a class="headerlink" href="#id3" title="姝ゆ爣棰樼殑姘镐箙閾炬帴">露</a></h2>
 <p>棣栧厛闇�瑕佸畨瑁匜unASR鍜孧odelScope. (<a class="reference external" href="https://alibaba-damo-academy.github.io/FunASR/en/installation.html">installation</a>)<br />
-鍩虹嚎绯荤粺鏈夎缁冨拰娴嬭瘯涓や釜鑴氭湰锛�<code class="docutils literal notranslate"><span class="pre">run.sh</span></code> 鏄敤浜庤缁冨熀绾跨郴缁熷苟鍦∕2MeT鐨勯獙璇佷笌娴嬭瘯闆嗕笂璇勪及鐨勶紝鑰� <code class="docutils literal notranslate"><span class="pre">run_m2met_2023_infer.sh</span></code> 鐢ㄤ簬姝ゆ绔炶禌棰勫寮�鏀剧殑鍏ㄦ柊娴嬭瘯闆嗕笂娴嬭瘯鍚屾椂鐢熸垚绗﹀悎绔炶禌鏈�缁堟彁浜ゆ牸寮忕殑鏂囦欢銆�
+鍩虹嚎绯荤粺鏈夎缁冨拰娴嬭瘯涓や釜鑴氭湰,<code class="docutils literal notranslate"><span class="pre">run.sh</span></code>鏄敤浜庤缁冨熀绾跨郴缁熷苟鍦∕2MeT鐨勯獙璇佷笌娴嬭瘯闆嗕笂璇勪及鐨勶紝鑰�<code class="docutils literal notranslate"><span class="pre">run_m2met_2023_infer.sh</span></code>鐢ㄤ簬姝ゆ绔炶禌棰勫寮�鏀剧殑鍏ㄦ柊娴嬭瘯闆嗕笂娴嬭瘯鍚屾椂鐢熸垚绗﹀悎绔炶禌鏈�缁堟彁浜ゆ牸寮忕殑鏂囦欢銆�
 鍦ㄨ繍琛� <code class="docutils literal notranslate"><span class="pre">run.sh</span></code>鍓嶏紝闇�瑕佽嚜琛屼笅杞藉苟瑙ｅ帇<a class="reference external" href="http://www.openslr.org/119/">AliMeeting</a>鏁版嵁闆嗗苟鏀剧疆浜�<code class="docutils literal notranslate"><span class="pre">./dataset</span></code>鐩綍涓嬶細</p>
 <div class="highlight-shell notranslate"><div class="highlight"><pre><span></span>dataset
 <span class="p">|</span>鈥斺��<span class="w"> </span>Eval_Ali_far
@@ -142,9 +142,10 @@
 <span class="p">|</span>鈥斺��<span class="w"> </span>Test_Ali_near
 <span class="p">|</span>鈥斺��<span class="w"> </span>Train_Ali_far
 <span class="p">|</span>鈥斺��<span class="w"> </span>Train_Ali_near
-鍦ㄨ繍琛�<span class="w"> </span><span class="sb">`</span>run_m2met_2023_infer.sh<span class="sb">`</span>鍓�,<span class="w"> </span>闇�瑕佸皢娴嬭瘯闆�<span class="sb">`</span>Test_2023_Ali_far<span class="sb">`</span>锛堜粎鍖呭惈闊抽锛屽皢浜�6.16鍙戝竷锛夋斁缃簬<span class="sb">`</span>./dataset<span class="sb">`</span>鐩綍涓嬨�傜劧鍚庡皢涓诲姙鏂规彁渚涚殑<span class="sb">`</span>wav.scp<span class="sb">`</span>锛�<span class="sb">`</span>wav_raw.scp<span class="sb">`</span>锛�<span class="sb">`</span>segments<span class="sb">`</span>锛�<span class="sb">`</span>utt2spk<span class="sb">`</span>鍜�<span class="sb">`</span>spk2utt<span class="sb">`</span>鏀剧疆浜�<span class="sb">`</span>./data/Test_2023_Ali_far<span class="sb">`</span>鐩綍涓嬨��
-<span class="sb">```</span>shell
-data/Test_2023_Ali_far
+</pre></div>
+</div>
+<p>鍦ㄨ繍琛�<code class="docutils literal notranslate"><span class="pre">run_m2met_2023_infer.sh</span></code>鍓�, 闇�瑕佸皢娴嬭瘯闆�<code class="docutils literal notranslate"><span class="pre">Test_2023_Ali_far</span></code>锛堜粎鍖呭惈闊抽锛屽皢浜�6.16鍙戝竷锛夋斁缃簬<code class="docutils literal notranslate"><span class="pre">./dataset</span></code>鐩綍涓嬨�傜劧鍚庡皢涓诲姙鏂规彁渚涚殑<code class="docutils literal notranslate"><span class="pre">wav.scp</span></code>锛�<code class="docutils literal notranslate"><span class="pre">wav_raw.scp</span></code>锛�<code class="docutils literal notranslate"><span class="pre">segments</span></code>锛�<code class="docutils literal notranslate"><span class="pre">utt2spk</span></code>鍜�<code class="docutils literal notranslate"><span class="pre">spk2utt</span></code>鏀剧疆浜�<code class="docutils literal notranslate"><span class="pre">./data/Test_2023_Ali_far</span></code>鐩綍涓嬨��</p>
+<div class="highlight-shell notranslate"><div class="highlight"><pre><span></span>data/Test_2023_Ali_far
 <span class="p">|</span>鈥斺��<span class="w"> </span>wav.scp
 <span class="p">|</span>鈥斺��<span class="w"> </span>wav_raw.scp
 <span class="p">|</span>鈥斺��<span class="w"> </span>segments
diff --git "a/docs/m2met2_cn/_build/html/\347\256\200\344\273\213.html" "b/docs/m2met2_cn/_build/html/\347\256\200\344\273\213.html"
index f9dc021..1f9d560 100644
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+++ "b/docs/m2met2_cn/_build/html/\347\256\200\344\273\213.html"
@@ -131,7 +131,7 @@
 <p>璇煶璇嗗埆锛圓utomatic Speech Recognition锛夈�佽璇濅汉鏃ュ織锛圫peaker Diarization锛夌瓑璇煶澶勭悊鎶�鏈殑鏈�鏂板彂灞曟縺鍙戜簡浼楀鏅鸿兘璇煶鐨勫箍娉涘簲鐢ㄣ�傜劧鑰屼細璁満鏅敱浜庡叾澶嶆潅鐨勫０瀛︽潯浠跺拰涓嶅悓鐨勮璇濋鏍硷紝鍖呮嫭閲嶅彔鐨勮璇濄�佷笉鍚屾暟閲忕殑鍙戣█鑰呫�佸ぇ浼氳瀹ょ殑杩滃満淇″彿浠ュ強鐜鍣０鍜屾贩鍝嶏紝浠嶇劧灞炰簬涓�椤规瀬鍏锋寫鎴樻�х殑浠诲姟銆�</p>
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