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IndicWav2Vec is a speech model pretrained on 17,000 hours of unlabelled audio across 40 Indian - languages, offering the most extensive language coverage among models tailored for Indian - languages.
- - - - February 2021 +IndicVoices 2.0 is a dataset of natural and spontaneous speech containing a total of 12000 hours of read (8%), extempore (76%) and conversational (15%) audio from 22563 speakers covering 208 Indian districts and 22 languages. Of these 12000 hours, 3200 hours have already been transcribed, with a median of 122 hours per language.
+ + + + June 2024Lorem ipsum dolor sit amet, consectetur adipisicing elit. Fugit excepturi accusamus minus - totam
- - - February 2021 +Lahaja is a benchmark featuring 12.5 hours of Hindi audio to facilitate a comprehensive assessment of Hindi ASR systems across various accents. This dataset includes read and spontaneous speech on diverse topics, collected from 132 speakers across 83 districts in India.
+ + + June 2024Lorem ipsum dolor sit amet, consectetur adipisicing elit. Fugit excepturi accusamus minus - totam
- - - March 2021 +IndicVoices 1.0 is a dataset of natural and spontaneous speech containing a total of 7348 hours of read (9%), extempore (74%) and conversational (17%) audio from 16237 speakers covering 145 Indian districts and 22 languages. Of these 7348 hours, 1639 hours have already been transcribed, with a median of 73 hours per language.
+ + + March 2024Lorem ipsum dolor sit amet, consectetur adipisicing elit. Fugit excepturi accusamus minus - totam
- - - April 2021 +Svarah is a benchmark addressing gaps in ASR performance on Indian accents, featuring 9.6 hours of transcribed English audio from 117 speakers across 65 locations in India. It includes both read and spontaneous speech across various domains, ensuring diverse vocabulary.
+ + + August 2023Lorem ipsum dolor sit amet, consectetur adipisicing elit. Fugit excepturi accusamus minus - totam
- - - April 2021 +IndicWhisper is finetuned on OpenAI’s Whisper model using the Vistaar-train set with over 10,000 hours across 12 Indian languages
+ + + July 2023Lorem ipsum dolor sit amet, consectetur adipisicing elit. Fugit excepturi accusamus minus - totam
- - - April 2021 +Kathbath is a comprehensive dataset comprising 1,684 hours of labeled speech data collected from 1,218 contributors across 203 districts in India, spanning 12 Indian languages.
+ + + February 2023Lorem ipsum dolor sit amet, consectetur adipisicing elit. Fugit excepturi accusamus minus - totam
- - - April 2021 +Shrutilipi is a dataset with 6,400+ hours of labeled audio across 12 Indian languages, totaling 4.95M sentences, created by mining text audio pairs from All India Radio.
+ + + August 2022Lorem ipsum dolor sit amet, consectetur adipisicing elit. Fugit excepturi accusamus minus - totam
- - - April 2021 +Dhwani is a unlabelled audio dataset consisting of 17,000 hours of raw speech data for 40 Indian languages from a wide variety of domains including education, news, technology, and finance
+ + + February 2022 + +IndicWav2Vec is a speech model pretrained on 17,000 hours of unlabelled audio across 40 Indian languages, offering the most extensive language coverage among models tailored for Indian languages.
+ + + February 2022