SpeechBrain
@SpeechBrain1
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#SpeechBrain is an all-in-one, open-source, PyTorch-based speech processing toolkit. https://t.co/yVH8WYKvyg
Joined January 2021
It's great to have FocalCodec in SpeechBrain! 📄 Paper: https://t.co/Wy8y0NvGxJ 💻 Training Code (SpeechBrain): https://t.co/rDDgkaXwIc 🎧 Pretrained Model: https://t.co/i6poMR2EDM 🔊 Demo Samples: https://t.co/gujaTUHE5q As always, true open-source, not just open weights!
huggingface.co
Unlock the magic of AI with handpicked models, awesome datasets, papers, and mind-blowing Spaces from lucadellalib
🚨 NeurIPS Alert! FocalCodec: an ultra-low bit-rate #speech tokenizer for multimodal #LLMs. Simple, Compact, and meaning-preserving. 📄 Paper by Luca Della Libera: https://t.co/bEZ4nXgJo2
@Concordia @Mila_Quebec
#NeurIPS #AI #DeepLearning #OpenSource
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Deadline Extended !!! The paper submission deadline for #IEEE MLSP 2025 is now April 29, 2025. We hope this gives more authors the chance to contribute! More info: https://t.co/zQoPvinxHu Please share! #MLSP2025 #MachineLearning #SignalProcessing #DeepLearning #CallForPapers
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Huge thanks to @NVIDIAAIDev for the NVIDIA Academic Grant #NVIDIAGrant! My team is already using the donated GPU hours on Saturn Cloud to accelerate our research. So grateful! #research #AI #SpeechBrain #GPU #A100 #DeepLearning #OpenSource #NVIDIA
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📢 Join our Conversational AI Reading Group! 📅 Thursday, March 13 | 11 AM - 12 PM EST 🎙Speaker: Alexandre Defossez @honualx 📖 Topic: "Moshi: a speech-text foundation model for real-time dialogue" 🔗 Details: ( https://t.co/oxEZtl9zYt)
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#IEEE MLSP 2025 – Call for Papers The OpenReview portal is now open! 📅 Deadline: April 22, 2025 🔗 Website: https://t.co/aQm0lJGfvW We welcome #papers on #deeplearning, #speech/#audio, #LLMs, #CV, #NLP, #EEG, #optimization, #fintech, #healthcare, #wireless comms, & more!
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My lab is running an amazing Reading Group on #ConversationalAI, open to all! This week (Feb 6, 11 AM EST) we host Hung-yi Lee, a top #AI researcher! He’ll talk about: "Teaching Foundation Models New Skills: Insights and Experiences". 🌍 Website: https://t.co/jVmfl49X86
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Our Speech-LLM diagnosis paper "What Are They Doing? Joint Audio-Speech Co-Reasoning" is accepted at #ICASSP 2025. Your model behaves more like an Audio-LLM or a Speech-LLM? See our specially designed task and dataset: Paper: https://t.co/aihhVxLzqN Github: https://t.co/qLefV92O7i
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We are working hard to organize the 35th #IEEE #MachineLearning for #SignalProcessing Workshop (MLSP) in #Istanbul (Aug 31–Sept 3, 2025)! It will be an unforgettable event with inspiring #research, talks, and keynotes. Paper submissions: Apr 22, 2025 https://t.co/S0Xvsm8gfA
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🌟To all #MachineLearning researchers: Join us in #Istanbul for the 35th #IEEE MLSP 2025 📅 Aug 31–Sept 3, 2025 We’re working hard to make this a memorable event in one of the world's most beautiful cities. https://t.co/S0Xvsm8O58
#DeepLearning #AI #NeuralNetworks #Research
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Fine-tuning #LLMs on domain-specific data doesn’t always improve performance, a challenge we call the "Adaptation Odyssey". Why does this happen? Our new #EMNLP2024 paper led by @firatoncell discusses this issue. 📄 https://t.co/9zeQrPDPck
#AI #NLP #DeepLearning
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This #NeurIPS2024 paper, co-authored with Francesco Paissan, Luca Della Libera, and Cem Subakan, is another step toward more interpretable #deeplearning for #audio classifiers. Read the paper here: https://t.co/byRy5vyf64 The code will be available soon in #SpeechBrain. #AI
I am happy to share that "Listenable Maps for Zero-Shot Audio Classifiers" has been accepted in #NeurIPS2024. The paper explores #explainability for #zeroshot classifiers. 📋 Paper: https://t.co/QyzLb4w5YX The code will be released soon!
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A long-term goal of #SpeechBrain is to enable natural human-machine communication, including #EEG support. #SpeechBrain-MOABB is a key first step in this direction, and it is now supporting EEG decoding tasks like motor imagery and more! #SpeechBrain #EEG #AI #DeepLearning
#SpeechBrain-MOABB is an #opensource library for benchmarking #DeepLearning models on #EEG signals with a robust, reproducible protocol. 📢 News: Our #paper is published in Computers in #Biology and #Medicine! 📝 Paper: https://t.co/U9N2bTFR6J 💻 Code: https://t.co/gZ7MfEoplD
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Great work by @MousaviPooneh on discrete audio tokens, a key component for multimodal #LLMs. Check out the #interspeech2024 paper: https://t.co/8Pq3MY9bIf Code now available in #SpeechBrain!
📢 I'll be presenting our paper "How Should We Extract Discrete Audio Tokens from Self-Supervised Models?" at InterSpeech! 🎙️ Meet us at the Speech Processing Using Discrete Speech Units, Oral Session on Sep 3, 16:20. 🔗 Paper: https://t.co/Z98B0DFjGD
#INTERSPEECH2024
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How can #LLMs improve the hypotheses generated by #ASR systems? This interesting paper by @AdaDTur , just accepted to SLT 2024, explores this idea. 🔗 https://t.co/vsR6cs7kzF
#DeepLearning #Speech #Audio #LLM #Researchpaper #AI #MachineLearning
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Amazing work @Francesco and Cem. The paper will be presented in an oral session at #iclm2024 and the code is available in #SpeechBrain! #deeplearning #AI #Audio #MachineLearning #NeuralNetworks
I am happy to announce that "Listenable Maps for Audio Classifiers" has been accepted at #icml2024 as an oral! Check out 👨💻 code in @Speechbrain1
https://t.co/Pb0c0OHmwK 🖥️ website https://t.co/FRF4HVwvSE 📖 paper: https://t.co/BpKS0NGvoE
#AI #deeplearning #audio #explainableAI
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I am happy to announce that "Listenable Maps for Audio Classifiers" has been accepted at #icml2024 as an oral! Check out 👨💻 code in @Speechbrain1
https://t.co/Pb0c0OHmwK 🖥️ website https://t.co/FRF4HVwvSE 📖 paper: https://t.co/BpKS0NGvoE
#AI #deeplearning #audio #explainableAI
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With the #NeurIPS2024 deadline behind us, it's time to start working on our next paper. ✍️ We are organizing #ANNPR2024 in Montreal at Concordia University. 🍁 The submission deadline is June 3rd. Details: https://t.co/JiRQJOqrDJ 🌐 #DeepLearning #researchpaper #AI
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The #IAPR Workshop on #NeuralNetworks in #PatternRecognition, known as #ANNPR2024, will occur this fall in Montreal at @Concordia. More info: https://t.co/JiRQJOpTOb Paper Submission: June 3, 2024. Don't miss out on contributing! #DeepLearning #AI #MachineLearning
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Quantization plays a crucial role in #deeplearning. It speeds up your model and reduces its memory footprint. Curious about how to implement it with #SpeechBrain? Check out Justin Lam's #tutorial: https://t.co/2j5MSGK5qt Explore all tutorials: https://t.co/CkYEluc8Lk
#AI
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🚀 SKILL is #deeplearning method for distilling knowledge from SSL models! 💡 Unlike traditional methods, SKILL distills across layer groups. Check out our paper presented at #ICASSP-#SAAB: https://t.co/gC4vdrAHXV Collaborative effort with EPFL and Sony. @lucazampierin #AI
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