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| Format: | Preprint |
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2025
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| Online-Zugang: | https://arxiv.org/abs/2501.15877 |
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| _version_ | 1866915268728455168 |
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| author | Batra, Ashita Narang, Mannas Sharma, Neeraj Kumar Das, Pradip K |
| author_facet | Batra, Ashita Narang, Mannas Sharma, Neeraj Kumar Das, Pradip K |
| contents | There is a growing need for diverse, high-quality stuttered speech data, particularly in the context of Indian languages. This paper introduces Project Boli, a multi-lingual stuttered speech dataset designed to advance scientific understanding and technology development for individuals who stutter, particularly in India. The dataset constitutes (a) anonymized metadata (gender, age, country, mother tongue) and responses to a questionnaire about how stuttering affects their daily lives, (b) captures both read speech (using the Rainbow Passage) and spontaneous speech (through image description tasks) for each participant and (c) includes detailed annotations of five stutter types: blocks, prolongations, interjections, sound repetitions and word repetitions. We present a comprehensive analysis of the dataset, including the data collection procedure, experience summarization of people who stutter, severity assessment of stuttering events and technical validation of the collected data. The dataset is released as an open access to further speech technology development. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_15877 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Boli: A dataset for understanding stuttering experience and analyzing stuttered speech Batra, Ashita Narang, Mannas Sharma, Neeraj Kumar Das, Pradip K Human-Computer Interaction Artificial Intelligence There is a growing need for diverse, high-quality stuttered speech data, particularly in the context of Indian languages. This paper introduces Project Boli, a multi-lingual stuttered speech dataset designed to advance scientific understanding and technology development for individuals who stutter, particularly in India. The dataset constitutes (a) anonymized metadata (gender, age, country, mother tongue) and responses to a questionnaire about how stuttering affects their daily lives, (b) captures both read speech (using the Rainbow Passage) and spontaneous speech (through image description tasks) for each participant and (c) includes detailed annotations of five stutter types: blocks, prolongations, interjections, sound repetitions and word repetitions. We present a comprehensive analysis of the dataset, including the data collection procedure, experience summarization of people who stutter, severity assessment of stuttering events and technical validation of the collected data. The dataset is released as an open access to further speech technology development. |
| title | Boli: A dataset for understanding stuttering experience and analyzing stuttered speech |
| topic | Human-Computer Interaction Artificial Intelligence |
| url | https://arxiv.org/abs/2501.15877 |