Top Tweets for #speechbrain
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
I'm happy to give a talk this Thursday on βDiscrete #Audio Tokens for Multimodal #LLMs" at the #ConversationalAI Reading Group at @Mila_Quebec .
It is open to everyone!
#DeepLearning #AI #LLM #SpeechBrain #Audio #Speech #Research #ConversationalAI
π’Join our last meeting of 2024 Conversational AI Reading Group on Thursday 19/12/2024, 11 AM-12 PM EST!
@mirco_ravanelli presents "Discrete Audio Tokens for Multimodal LLMs"
Details: https://t.co/5EOuxyeNg0
You could also follow us on BlueSky : https://t.co/XRpwz4LZta
'Open-Source Conversational AI with SpeechBrain 1.0', by Mirco Ravanelli et al.
https://t.co/D0EKx8rQBv
#speechbrain #speech #conversational
π§ #SpeechBrain-MOABB, our #opensource #EEG benchmark, is designed to test #DeepLearning models across tasks with a robust protocol for fair comparison!
π Our latest #paper: https://t.co/SEwFR60AOd
(just accepted in Neural Networks!)
π» Code: https://t.co/HDUHzQrSBE
#AI
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.
π Paper: https://t.co/QyzLb4w5YX
The code will be released soon!
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.
π’ News: Our #paper is published in Computers in #Biology and #Medicine!
π Paper: https://t.co/U9N2bTFR6J
π» Code: https://t.co/gZ7MfEoplD
#SpeechBrain-MOABB is an #opensource library for benchmarking #DeepLearning models on #EEG signals with a robust, reproducible protocol.
π’ News: Our #paper is published in Computers in #Biology and #Medicine!
π Paper: https://t.co/U9N2bTFR6J
π» Code: https://t.co/gZ7MfEoplD
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!
π’ I'll be presenting our paper "How Should We Extract Discrete Audio Tokens from Self-Supervised Models?" at InterSpeech! ποΈ
Meet us at the Speech Processing Using Discrete Speech Units, Oral Session on Sep 3, 16:20.
π Paper: https://t.co/Z98B0DFjGD
#INTERSPEECH2024
If you're attending #INTERSPEECH2024 and have an interest in audio tokens, we warmly invite you to join our presentation!
#DeepLearning #Speech #LLM #audio #research #SpeechBrain #AI
π’ I'll be presenting our paper "How Should We Extract Discrete Audio Tokens from Self-Supervised Models?" at InterSpeech! ποΈ
Meet us at the Speech Processing Using Discrete Speech Units, Oral Session on Sep 3, 16:20.
π Paper: https://t.co/Z98B0DFjGD
#INTERSPEECH2024
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
π¨βπ» code in @Speechbrain1 https://t.co/Pb0c0OHmwK
π₯οΈ website https://t.co/FRF4HVwvSE
π paper: https://t.co/BpKS0NGvoE
#AI #deeplearning #audio #explainableAI
π Huge congrats to @fpaissan_ and @CemSubakan on this amazing work on Interepretable #DeepLearning for #Audio!
It will be presented at #icml2024 in an oral session. Even better, the code is in #SpeechBrain.
π Paper: https://t.co/e1M1SvPdPD
π Code: https://t.co/liIhgErEuj
I am happy to announce that "Listenable Maps for Audio Classifiers" has been accepted at #icml2024 as an oral!
Check out
π¨βπ» code in @Speechbrain1 https://t.co/Pb0c0OHmwK
π₯οΈ website https://t.co/FRF4HVwvSE
π paper: https://t.co/BpKS0NGvoE
#AI #deeplearning #audio #explainableAI
Are you interested in #ConversationalAI?
#SpeechBrain is an #OpenSource toolkit designed to make #research on #ConversationalAI faster and simpler with a focus on speech processing. Learn more about @SpeechBrain1 in the latest Mila Blog by @Mirco Ravanelli https://t.co/PtPQmaLSTv
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
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
π°Have you seen our paper @ IWSDS2024 on the robustness of LLMs for spoken dialogues?? https://t.co/f9ckwWlB6T
We did that study via #SpeechBrain, A well-documented open-source toolkit for Processing Speechπ¬,Audioπ, Textπ°. And today the new version is out!
Exciting news! π #SpeechBrain 1.0 is out with tons of thrilling advancements.
Our #OpenSource toolkit now features 200+ recipes and 100+ pretrained models on #HuggingFace for diverse #ConversationalAI tasks.
π Website: https://t.co/a1wqxLucgw
π» Repo: https://t.co/MsCZbSbSOf
Delighted to see the release of #SpeechBrain 1.0 π -- Flower and SpeechBrain have been collaborating since 2021, and together they are the easiest way to federate any speech or audio model.
Try out the SpeechBrainβFlower demo, upgraded especially for today's 1.0 relase by Flower Labs Research Scientist Yan Gao (@yangao381) π, link below.
https://t.co/hSG5N8qR1j
Exciting news! π #SpeechBrain 1.0 is out with tons of thrilling advancements.
Our #OpenSource toolkit now features 200+ recipes and 100+ pretrained models on #HuggingFace for diverse #ConversationalAI tasks.
π Website: https://t.co/a1wqxLucgw
π» Repo: https://t.co/MsCZbSbSOf
#SpeechBrain is legit one of the best open source toolkits for voice AI. Congrats to the team for entering the v1 club π
Exciting news! π #SpeechBrain 1.0 is out with tons of thrilling advancements.
Our #OpenSource toolkit now features 200+ recipes and 100+ pretrained models on #HuggingFace for diverse #ConversationalAI tasks.
π Website: https://t.co/a1wqxLucgw
π» Repo: https://t.co/MsCZbSbSOf
#SpeechBrain 1.0 is finally out!
If you're into speech research, you should have a look at the new features and recipes proposed. I am particularly excited about what people will build with the K2 integration, the new search methods, and the whole new "Benchmarks" section.
Exciting news! π #SpeechBrain 1.0 is out with tons of thrilling advancements.
Our #OpenSource toolkit now features 200+ recipes and 100+ pretrained models on #HuggingFace for diverse #ConversationalAI tasks.
π Website: https://t.co/a1wqxLucgw
π» Repo: https://t.co/MsCZbSbSOf
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