Today, speech technology is only available for a small fraction of the thousands of languages spoken around the world because traditional systems need to be trained on large amounts of annotated speech audio with transcriptions. Obtaining that kind of data for every human language and dialect is almost impossible.
Wav2vec works around this limitation by requiring little to no transcribed data. The model uses self-supervision to push the boundaries by learning from unlabeled training data. This enables speech recognition systems for many more languages and dialects, such as Kyrgyz and Swahili, which don’t have a lot of transcribed speech audio. Self-supervision is the key to leveraging unannotated data and building better systems.
הילמ"ה- הייטק למען החברה, היא חברה לתועלת הציבור וללא מטרות רווח, שהוקמה ב-2018 על ידי בכירים בעולם ההיי-טק הישראלי, המבקשים להפוך את ישראל למובילה עולמית בתחום חדשנות האימפקט,
על מנת לתת מענה לאתגרים ציבוריים וחברתיים.
הילמ"ה הוקמה בהשראת יחידת 8200 הצה"לית, והיא מכשירה דור של צעירות וצעירים מוכשרים ושאפתנים לפיתוח פתרונות טכנולוגיים-חברתיים פורצי דרך לתועלת החברה.
הפתרונות של הילמ"ה מתוכננים בהתאמה מלאה לצורכי החינוך, הרווחה והבריאות, ומתקבלים באהדה רבה על ידי לקוחות, קולגות ושותפים לדרך.
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