Top Tweets for #diarization
Speaker Diarization = “Who spoke when?”
It segments audio by speaker identity , crucial for meetings, call analytics, and podcasts.
Try it with PyAnnote, a powerful open-source toolkit for diarization.
#AI #SpeechRecognition #PyAnnote #Diarization #DeepLearning #AudioAI
Where conversations happen, speaker intelligence should follow. pyannoteAI is now available on-device, thanks to our partnership with
@argmax
🎉Run our most accurate speaker diarization models at the edge. 📷 More in the comments #VoiceAI #PrivacyFirst #Diarization #AI
◤ mocoVoice APIは話者分離機能に対応しました！ ◢
誰が話したかがわかるようになりました
👨🦰💬
👩💬
👨🦳💬
👧💬
mocoVoice APIの利用開始はこちらから👉https://t.co/YDPFWsNtOj
#話者分離 #Diarization #音声認識 #生成AI
https://t.co/RMtqju4FJx
mocomoco、音声認識AI「mocoVoice API」に話者分離機能を追加！ https://t.co/7eCcpIk19U
What if #pyannote could do separation too? 🔀
I am hiring a postdoc to help me with that! 👩🎓
Apply here: https://t.co/7Qs93TXCag
… or please RT 🙏
#diarization #pyannote
Off to Dublin for Interspeech 2023! Looking forward to the conference, and having some good chats about diarization
#interspeech #interspeech2023 #diarization
🫨 "Who said what?!"
Transcriptions of Video Calls are nice but they aren't very useful if you can't tell which speaker said what. With speaker diariztion you can! 🫎 @wassamatta_u shows how in this demo app #webrtc #diarization #ASR
https://t.co/gR3Vgk6rWg
Idasco Team (Department of Computer Science, Faculty of Science, University of Yaounde I) is working on Xdiar #explainability for #diarization #JSATL2023
Très heureux d’avoir pu présenter mon travail sur les #LLM et la #diarization pour la journée des doctorants de Paris Saclay dans les locaux d’@AgroParisTech ! Beaucoup d’échanges très intéressants
🫨 "Who said what?!"
Transcriptions of Video Calls are nice but they aren't very useful if you can't tell which speaker said what. With speaker diariztion you can! 🫎 @wassamatta_u shows how in this demo app #webrtc #diarization #ASR
https://t.co/jQ3PQFf8ji
📢Sharing my new tutorial on how to combine #diart with @OpenAI's Whisper for🌈speaker-colored transcriptions in real-time!
🔥Check out the demo below! #SpeechProc #diarization
📗Blog post: https://t.co/NtiWUEuJ5I
💻Code: https://t.co/MaX5Hx8qWL
Missed my PhD defense on Continual Representation Learning in Written and Spoken Language last week?
No worries! Slides are now available here: https://t.co/A2OFy41B8j
Thank you Sophie Rosset, @hbredin and @Sahar_ghannay for your amazing supervision!
#NLP #diarization
Oyez, oyez, fellow #diarization aficionados!
@juanmc2005 will defend his PhD thesis about continual learning and its application to NLP and (online) speaker diarization.
When? April 5th, 2PM (CEST).
Where? at @LisnLab or online (link below)
https://t.co/52jyuhAcLY
The publication “Bayesian HMM clustering of x-vector sequences (VBx) in speaker diarization: Theory, implementation and analysis on standard tasks” by Federico Landini. made it to the top cited articles from Computer speech and Language!
#diarization
https://t.co/CVVGf8WBuD
“Who spoke when?"
State of Speaker Diarization in 2022: https://t.co/ssVqdMtnQ6
#Diarization #SpeakerDiarization #VoiceRecognition #VoiceAI #VoiceTech #VoiceFirst
The #Diarization feature enhances #transcript readability by identifying speaker changes.
Here's a breakdown of how it works and including its common applications. 👇
https://t.co/ZtfMFakObC
#transcription #API
The dataset and benchmarks will help with long-term research on Ego-centric perception. Audio and speech folks might be specially interested in our Audio-Visual Diarization benchmark. #speech, #diarization
This week's INTERSPEECH!
https://t.co/mE6hMijnpM
#speechrecognition #speechprocessing #diarization #AI #ML #hitachi
3/3
Koichiro Ito, Takuya Fujioka, Qinghua Sun, and Kenji Nagamatsu, Audio-Visual Speech Emotion Recognition by Disentangling Emotion and Identity Attributes
This paper is on multimodal emotion recognition based on representation disentanglement.
Congrats, Ito-san!
#childspeech #diarization: in a 2x2x2x3x2x2 experimental test, one of the variables tested is the strategy for multiple instance learning. Best result gets a diarization error rate of 43.8%. https://t.co/4eunCkLxHi, #ICASSP2021
Even accurate speech recognition can be confusing without accurate *diarization*, or the marking of speaker turn changes. Read about Cobalt's recent work in this area in this week's CoBlog entry.
#SpeechTech #diarization #ASR
https://t.co/dA86BWGKUh
Check out our work "On The Impact Of Language Familiarity In Talker Change Detection" at #ICASSP2020 @IEEEsps. This work started @TELNeuromorphs ⛰️
Conference paper: https://t.co/u5V9ZCEjTM
Talk: https://t.co/VdxHG0HEYS
#language #familiarity #machine #diarization
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