3 citations · 5 across the 11 of their papers we have counts for
5 papers · 1 filter
The Balancing Act: Unmasking and Alleviating ASR Biases in Portuguese
Ajinkya Kulkarni, Anna Tokareva, Rameez Qureshi +1
In the field of spoken language understanding, systems like Whisper and Multilingual Massive Speech (MMS) have shown state-of-the-art performances. This study is dedicated to a com…
ArTST: Arabic Text and Speech Transformer
Hawau Olamide Toyin, Amirbek Djanibekov, Ajinkya Kulkarni +1
We present ArTST, a pre-trained Arabic text and speech transformer for supporting open-source speech technologies for the Arabic language. The model architecture follows the unifie…
Yet Another Model for Arabic Dialect Identification
Ajinkya Kulkarni, Hanan Aldarmaki
In this paper, we describe a spoken Arabic dialect identification (ADI) model for Arabic that consistently outperforms previously published results on two benchmark datasets: ADI-5…
Adapting the adapters for code-switching in multilingual ASR
Atharva Kulkarni, Ajinkya Kulkarni, Miguel Couceiro +1
Recently, large pre-trained multilingual speech models have shown potential in scaling Automatic Speech Recognition (ASR) to many low-resource languages. Some of these models emplo…
ClArTTS: An Open-Source Classical Arabic Text-to-Speech Corpus
Ajinkya Kulkarni, Atharva Kulkarni, Sara Abedalmonem Mohammad Shatnawi +1
At present, Text-to-speech (TTS) systems that are trained with high-quality transcribed speech data using end-to-end neural models can generate speech that is intelligible, natural…