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Evaluating Sampling-based Filler Insertion with Spontaneous TTS
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Speech, Music and Hearing, TMH.
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Speech, Music and Hearing, TMH.ORCID iD: 0000-0002-0397-6442
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Speech, Music and Hearing, TMH.ORCID iD: 0000-0003-1175-840X
2022 (English)In: LREC 2022: Thirteen International Conference On Language Resources And Evaluation / [ed] Calzolari, N Bechet, F Blache, P Choukri, K Cieri, C Declerck, T Goggi, S Isahara, H Maegaard, B Mazo, H Odijk, H Piperidis, S, European Language Resources Association (ELRA) , 2022, p. 1960-1969Conference paper, Published paper (Refereed)
Abstract [en]

Inserting fillers (such as "um", "like") to clean speech text has a rich history of study. One major application is to make dialogue systems sound more spontaneous. The ambiguity of filler occurrence and inter-speaker difference make both modeling and evaluation difficult. In this paper, we study sampling-based filler insertion, a simple yet unexplored approach to inserting fillers. We propose an objective score called Filler Perplexity (FPP). We build three models trained on two single-speaker spontaneous corpora, and evaluate them with FPP and perceptual tests. We implement two innovations in perceptual tests, (1) evaluating filler insertion on dialogue systems output, (2) synthesizing speech with neural spontaneous TTS engines. FPP proves to be useful in analysis but does not correlate well with perceptual MOS. Perceptual results show little difference between compared filler insertion models including with ground-truth, which may be due to the ambiguity of what is good filler insertion and a strong neural spontaneous TTS that produces natural speech irrespective of input. Results also show preference for filler-inserted speech synthesized with spontaneous TTS. The same test using TTS based on read speech obtains the opposite results, which shows the importance of using spontaneous TTS in evaluating filler insertions. Audio samples: www.speech.kth.se/tts- demos/LREC22

Place, publisher, year, edition, pages
European Language Resources Association (ELRA) , 2022. p. 1960-1969
Keywords [en]
filler insertion, spontaneous text-to-speech, spoken dialogue system
National Category
Natural Language Processing
Identifiers
URN: urn:nbn:se:kth:diva-324340ISI: 000889371702007Scopus ID: 2-s2.0-85144345531OAI: oai:DiVA.org:kth-324340DiVA, id: diva2:1740010
Conference
13th International Conference on Language Resources and Evaluation (LREC), JUN 20-25, 2022, Marseille, FRANCE
Note

QC 20230228

Available from: 2023-02-28 Created: 2023-02-28 Last updated: 2025-02-07Bibliographically approved

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Wang, SiyangGustafsson, JoakimSzékely, Éva

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