Identifying speakers in children's stories for speech synthesis

By Jason Y. Zhang, Alan W. Black, Richard Sproat. 2003

52 citations recorded by the source corpus.

Choosing appropriate voices for synthesizing children’s stories requires text analysis techniques that can identify which portions of the text should be read by which speakers. Our work presents techniques to take raw text stories and automatically identify the quoted speech, identify the characters within the stories and assign characters to each quote. The resulting marked-up story may then be rendered with a standard speech synthesizer with appropriate voices for the characters. This paper presents each of the basic stages in identification, and the algorithms, both rule-driven and data-driven, used to achieve this. A variety of story texts are used to test our system. Results are presented with a discussion of the limitations and recommendations on how to improve speaker assignment in further texts.

Subfields: Artificial Intelligence, Speech & Audio

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Citations in the corpus

Towards Unsupervised Speech Recognition and Synthesis with Quantized Speech Representation Learning (2019, methodology): “For the linguistic units, CMU phoneme set [20] is used for grapheme to phoneme conversion [21].”
The CMU Arctic speech databases (2004, background): “CMU-DICT has three levels of stress while Fest-Dict distinguishes only two.”