30 citations · 92 across the 17 of their papers we have counts for
19 papers
Dual-Pipeline with Low-Rank Adaptation for New Language Integration in Multilingual ASR
Yerbolat Khassanov, Zhipeng Chen, Tianfeng Chen +5
This paper addresses challenges in integrating new languages into a pre-trained multilingual automatic speech recognition (mASR) system, particularly in scenarios where training da…
Multilingual Text-to-Speech Synthesis for Turkic Languages Using Transliteration
Rustem Yeshpanov, Saida Mussakhojayeva, Yerbolat Khassanov
This work aims to build a multilingual text-to-speech (TTS) synthesis system for ten lower-resourced Turkic languages: Azerbaijani, Bashkir, Kazakh, Kyrgyz, Sakha, Tatar, Turkish,…
Random Utterance Concatenation Based Data Augmentation for Improving Short-video Speech Recognition
Yist Y. Lin, Tao Han, Haihua Xu +6
One of limitations in end-to-end automatic speech recognition (ASR) framework is its performance would be compromised if train-test utterance lengths are mismatched. In this paper,…
KazakhTTS2: Extending the Open-Source Kazakh TTS Corpus With More Data, Speakers, and Topics
Saida Mussakhojayeva, Yerbolat Khassanov, Huseyin Atakan Varol
We present an expanded version of our previously released Kazakh text-to-speech (KazakhTTS) synthesis corpus. In the new KazakhTTS2 corpus, the overall size has increased from 93 h…
KazNERD: Kazakh Named Entity Recognition Dataset
Rustem Yeshpanov, Yerbolat Khassanov, Huseyin Atakan Varol
We present the development of a dataset for Kazakh named entity recognition. The dataset was built as there is a clear need for publicly available annotated corpora in Kazakh, as w…
A Study of Multimodal Person Verification Using Audio-Visual-Thermal Data
Madina Abdrakhmanova, Saniya Abushakimova, Yerbolat Khassanov +1
In this paper, we study an approach to multimodal person verification using audio, visual, and thermal modalities. The combination of audio and visual modalities has already been s…
A Study of Multilingual End-to-End Speech Recognition for Kazakh, Russian, and English
Saida Mussakhojayeva, Yerbolat Khassanov, Huseyin Atakan Varol
We study training a single end-to-end (E2E) automatic speech recognition (ASR) model for three languages used in Kazakhstan: Kazakh, Russian, and English. We first describe the dev…
USC: An Open-Source Uzbek Speech Corpus and Initial Speech Recognition Experiments
Muhammadjon Musaev, Saida Mussakhojayeva, Ilyos Khujayorov +3
We present a freely available speech corpus for the Uzbek language and report preliminary automatic speech recognition (ASR) results using both the deep neural network hidden Marko…
KazakhTTS: An Open-Source Kazakh Text-to-Speech Synthesis Dataset
Saida Mussakhojayeva, Aigerim Janaliyeva, Almas Mirzakhmetov +2
This paper introduces a high-quality open-source speech synthesis dataset for Kazakh, a low-resource language spoken by over 13 million people worldwide. The dataset consists of ab…
SpeakingFaces: A Large-Scale Multimodal Dataset of Voice Commands with Visual and Thermal Video Streams
Madina Abdrakhmanova, Askat Kuzdeuov, Sheikh Jarju +3
We present SpeakingFaces as a publicly-available large-scale multimodal dataset developed to support machine learning research in contexts that utilize a combination of thermal, vi…
Enriching Under-Represented Named-Entities To Improve Speech Recognition Performance
Tingzhi Mao, Yerbolat Khassanov, Van Tung Pham +4
Automatic speech recognition (ASR) for under-represented named-entity (UR-NE) is challenging due to such named-entities (NE) have insufficient instances and poor contextual coverag…
A Crowdsourced Open-Source Kazakh Speech Corpus and Initial Speech Recognition Baseline
Yerbolat Khassanov, Saida Mussakhojayeva, Almas Mirzakhmetov +3
We present an open-source speech corpus for the Kazakh language. The Kazakh speech corpus (KSC) contains around 332 hours of transcribed audio comprising over 153,000 utterances sp…
Leveraging Text Data Using Hybrid Transformer-LSTM Based End-to-End ASR in Transfer Learning
Zhiping Zeng, Van Tung Pham, Haihua Xu +4
In this work, we study leveraging extra text data to improve low-resource end-to-end ASR under cross-lingual transfer learning setting. To this end, we extend our prior work [1], a…
Approaches to Improving Recognition of Underrepresented Named Entities in Hybrid ASR Systems
Tingzhi Mao, Yerbolat Khassanov, Van Tung Pham +3
In this paper, we present a series of complementary approaches to improve the recognition of underrepresented named entities (NE) in hybrid ASR systems without compromising overall…
Independent language modeling architecture for end-to-end ASR
Van Tung Pham, Haihua Xu, Yerbolat Khassanov +5
The attention-based end-to-end (E2E) automatic speech recognition (ASR) architecture allows for joint optimization of acoustic and language models within a single network. However,…
Constrained Output Embeddings for End-to-End Code-Switching Speech Recognition with Only Monolingual Data
Yerbolat Khassanov, Haihua Xu, Van Tung Pham +4
The lack of code-switch training data is one of the major concerns in the development of end-to-end code-switching automatic speech recognition (ASR) models. In this work, we propo…
Enriching Rare Word Representations in Neural Language Models by Embedding Matrix Augmentation
Yerbolat Khassanov, Zhiping Zeng, Van Tung Pham +2
The neural language models (NLM) achieve strong generalization capability by learning the dense representation of words and using them to estimate probability distribution function…
On the End-to-End Solution to Mandarin-English Code-switching Speech Recognition
Zhiping Zeng, Yerbolat Khassanov, Van Tung Pham +3
Code-switching (CS) refers to a linguistic phenomenon where a speaker uses different languages in an utterance or between alternating utterances. In this work, we study end-to-end…
Unsupervised and Efficient Vocabulary Expansion for Recurrent Neural Network Language Models in ASR
Yerbolat Khassanov, Eng Siong Chng
In automatic speech recognition (ASR) systems, recurrent neural network language models (RNNLM) are used to rescore a word lattice or N-best hypotheses list. Due to the expensive t…