Expressive Text-to-Speech Synthesis using Text Chat Dataset with Speaking Style Information Article Swipe
Yukinori Homma
,
Hiroki Kanagawa
,
Nozomi Kobayashi
,
Yusuke Ijima
,
Kuniko Saito
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1527/tjsai.38-3_f-ma7
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1527/tjsai.38-3_f-ma7
This paper aims to generate expressive speech for integration with a robot and AI character dialogue systems. To generate expressive speech, some researchers have proposed using labels that express specific dialogue acts and emotions (i.e., speaking style information). Our approach is to use the speaking style information as an intermediate representation and to train a model for inferring the speaking style information from the text and a speech synthesis model independently. Using a model that infers speaking style information from text, we construct a method that can generate expressive speech for text in the dialogue domain, outside the scope of speech synthesis training. The method first estimates the labels corresponding to the speaking style information for the input text. Then, the estimated labels and the input text are used to generate speech using a speech synthesis model. Experiments show that our method effectively improves the accuracy of text classification of speaking style labels. Subjective evaluation experiments show that our method can produce more expressive speech than conventional methods.
Related Topics
Concepts
Computer science
Style (visual arts)
Speech synthesis
Natural language processing
Construct (python library)
Speech recognition
Artificial intelligence
Representation (politics)
Scope (computer science)
Character (mathematics)
History
Politics
Archaeology
Programming language
Political science
Mathematics
Geometry
Law
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1527/tjsai.38-3_f-ma7
- https://www.jstage.jst.go.jp/article/tjsai/38/3/38_38-3_F-MA7/_pdf
- OA Status
- diamond
- References
- 24
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4367555999
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4367555999Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1527/tjsai.38-3_f-ma7Digital Object Identifier
- Title
-
Expressive Text-to-Speech Synthesis using Text Chat Dataset with Speaking Style InformationWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-04-30Full publication date if available
- Authors
-
Yukinori Homma, Hiroki Kanagawa, Nozomi Kobayashi, Yusuke Ijima, Kuniko SaitoList of authors in order
- Landing page
-
https://doi.org/10.1527/tjsai.38-3_f-ma7Publisher landing page
- PDF URL
-
https://www.jstage.jst.go.jp/article/tjsai/38/3/38_38-3_F-MA7/_pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
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diamondOpen access status per OpenAlex
- OA URL
-
https://www.jstage.jst.go.jp/article/tjsai/38/3/38_38-3_F-MA7/_pdfDirect OA link when available
- Concepts
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Computer science, Style (visual arts), Speech synthesis, Natural language processing, Construct (python library), Speech recognition, Artificial intelligence, Representation (politics), Scope (computer science), Character (mathematics), History, Politics, Archaeology, Programming language, Political science, Mathematics, Geometry, LawTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- References (count)
-
24Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| referenced_works | https://openalex.org/W2962691331, https://openalex.org/W3160329778, https://openalex.org/W3197034238, https://openalex.org/W2973217961, https://openalex.org/W2787685498, https://openalex.org/W3107262928, https://openalex.org/W4224925626, https://openalex.org/W3081488690, https://openalex.org/W1965255698, https://openalex.org/W2966387353, https://openalex.org/W4226230180, https://openalex.org/W2903739847, https://openalex.org/W2118774185, https://openalex.org/W3196027980, https://openalex.org/W4323642664, https://openalex.org/W3155584966, https://openalex.org/W2964243274, https://openalex.org/W2314352174, https://openalex.org/W2885800352, https://openalex.org/W3115920274, https://openalex.org/W2741630455, https://openalex.org/W3201197320, https://openalex.org/W2808336242, https://openalex.org/W2545596629 |
| referenced_works_count | 24 |
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| abstract_inverted_index.To | 17 |
| abstract_inverted_index.an | 48 |
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| abstract_inverted_index.to | 3, 41, 52, 110, 129 |
| abstract_inverted_index.we | 81 |
| abstract_inverted_index.Our | 38 |
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| abstract_inverted_index.for | 7, 56, 90, 115 |
| abstract_inverted_index.our | 140, 158 |
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| abstract_inverted_index.show | 138, 156 |
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| abstract_inverted_index.domain, | 95 |
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| abstract_inverted_index.methods. | 167 |
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| abstract_inverted_index.experiments | 155 |
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| abstract_inverted_index.intermediate | 49 |
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| abstract_inverted_index.independently. | 70 |
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| cited_by_percentile_year | |
| countries_distinct_count | 1 |
| institutions_distinct_count | 5 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/4 |
| sustainable_development_goals[0].score | 0.5299999713897705 |
| sustainable_development_goals[0].display_name | Quality Education |
| citation_normalized_percentile.value | 0.04846692 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |