74 citations · 111 across the 33 of their papers we have counts for
9 papers · 1 filter
Automatic Restoration of Diacritics for Speech Data Sets
Sara Shatnawi, Sawsan Alqahtani, Hanan Aldarmaki
Automatic text-based diacritic restoration models generally have high diacritic error rates when applied to speech transcripts as a result of domain and style shifts in spoken lang…
Spoken Word2Vec: Learning Skipgram Embeddings from Speech
Mohammad Amaan Sayeed, Hanan Aldarmaki
Text word embeddings that encode distributional semantics work by modeling contextual similarities of frequently occurring words. Acoustic word embeddings, on the other hand, typic…
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…
Handling Realistic Label Noise in BERT Text Classification
Maha Tufail Agro, Hanan Aldarmaki
Labels noise refers to errors in training labels caused by cheap data annotation methods, such as web scraping or crowd-sourcing, which can be detrimental to the performance of sup…
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…
Diacritic Recognition Performance in Arabic ASR
Hanan Aldarmaki, Ahmad Ghannam
We present an analysis of diacritic recognition performance in Arabic Automatic Speech Recognition (ASR) systems. As most existing Arabic speech corpora do not contain all diacriti…
Supervised Acoustic Embeddings And Their Transferability Across Languages
Sreepratha Ram, Hanan Aldarmaki
In speech recognition, it is essential to model the phonetic content of the input signal while discarding irrelevant factors such as speaker variations and noise, which is challeng…