الصوتيات العربية – A community for all Arabic speakers to enhance arabic speech research

— المنتديات التقنية

الإجتماع السنوي لتحدي MGB

— مصادر الأصوات العربية

نسعى معا لزياده جودة محتوى الصوتيات العربية

— تقنيات الأصوات

التقنيات الداعمة لعلم الأصوات

من نحن

مجتمع الصوتيات العربية تهدف الى زيادة المنفعة العلمية في مجال تقنيات الصوتيات العربية و تسعى لدعم المجتمعات العربية الناطقة بلهجات عربية مختلفة. مجتمع الصوتيات العربية يهتم بتقنيات الصوتيات العربية و أيضا بمعالجة اللغة العربية، هدفنا الرئيسي هو دعم اللغة العربية الفصحى و اللهجات المتعددة. مجتمع الصوتيات العربية سوف يدعم بناء تقنيات اللغة العربية و الاختراعات التي تتمركز حول صوتيات اللغة العربية، نحن نقوم بعمل مسابقات تقنية كبيرة في مجال الصوتيات العربية المختلفة لنخرج منها بنتائج ملموسة تؤثر في حياة الأشخاص. نحن نهتم بكلا الجانبية العلمي و العملي فنقدم الأبحاث العملية و التطبيقات العملية التي تستخدم في سوق العمل، سوف ندعم جاهدا تقنيات الصوتيات العربية لتكون تقنية عالمية تستخدم في جميع المجالات.

التعرف التلقائي على الأصوات

Automatic Speech Recognition (ASR) is the process of converting the speech signal into its corresponding text. The quality of ASR systems is measured by how close their recognized sequences of words are to human recognized sequences of words.

لهجات اللغة العربية

Dialect identification (DID) is a special case of Language identification (LID) problem. This is the process of automatically identifying the language class for a given speech segment.

نص إلى صوت

The Text to Speech (TTS) technology aims to convert a sequence of words into speech.

نماذج اللغة

Language Models are building block of many speech and NLP technology that aims at accurately estimating the probability distribution of a word sequences or sentences produced in a natural language

لقاءاتنا

يونيو

يوليو 2021

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Events for يوليو

31st

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Arabic SpeechFollow

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Kanari AI @kanari_ai·

19 يوليو

We are excited to share our new speech recognition milestone:
Multi-lingual, multi-dialectal Arabic speech recognition.
Joint research with @qatarcomputing @hbku
Coming soon at @interspeech2021

@arabicspeech

https://vimeo.com/576852871/932f1351c0

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Michael Auli @MichaelAuli·

21 مايو

Today we are announcing our work on building speech recognition models without any labeled data! wav2vec-U rivals some of the best supervised systems from only two years ago.

Paper: https://ai.facebook.com/research/publications/unsupervised-speech-recognition
Blog: https://ai.facebook.com/blog/wav2vec-unsupervised-speech-recognition-without-supervision
Code: https://github.com/pytorch/fairseq/tree/master/examples/wav2vec/unsupervised

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Yann LeCun @ylecun·

21 مايو

Wave2vec-Unsupervised is particularly useful for languages, dialects, and accents for which little or no transcribed data is available.
Here is an example demo in Swahili. https://twitter.com/MichaelAuli/status/1395774305372237825

Michael Auli@MichaelAuli

It also works in languages other than English, see the Swahili demo below. So far we tried it on Kyrgyz, Tatar, German, Dutch, French, Spanish, Portuguese, Italian.

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SpeechBrain @SpeechBrain1·

15 مارس

Thanks, @mircoravanelli!
I hope I can be helpful to all the developers of #speech technologies that are looking for a simple and intuitive #opensource toolkit. I still support many #speech tasks and, with a bigger community, I can keep growing!

https://speechbrain.github.io/ https://twitter.com/mirco_ravanelli/status/1371464761536348161

Mirco Ravanelli@mirco_ravanelli

I'm thrilled to announce the public release of #SpeechBrain!

#SpeechBrain is an #opensource toolkit designed to make research and development of #speech technologies faster. It is flexible, modular, easy-to-use, well documented.

https://speechbrain.github.io/

#DeepLearning #AI

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🔥 Kareem Carr 🔥@kareem_carr·

27 مارس

FOUR things to know about race and gender bias in algorithms:

1. The bias starts in the data

2. The algorithms don't create the bias but they do transmit it

3. There are a huge number of other biases. Race and gender bias are just the most obvious

4. It's fixable! 🧵👇

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