Multilingual processing of speech via web services
By T. Kisler, U. Reichel, Florian Schiel. Computer Speech and Language, 2017
529 citations recorded by the source corpus.
Subfields: Artificial Intelligence
View Paper: https://www.semanticscholar.org/paper/31d4acbcaa0bd0a5bc5f3fdec56d36f6fbb61b29
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In Artificial Intelligence
- Zhaoxi Mu
- Xinyu Yang
- Yizhuo Dong
- William N. Havard
- Laurent Besacier
- Laurent Girin
- Brooke Stephenson
- Thomas Hueber
Citations in the corpus
- Review of end-to-end speech synthesis technology based on deep learning (2021, background): “Finally, the speech segments will be cropped [104] and spliced.”
- What the Future Brings: Investigating the Impact of Lookahead for Incremental Neural TTS (2020, methodology): “Then, using the Munich Automatic Segmentation system [21] (an automatic speech recognition and forced alignment tool which employs an HMM and Viterbi decoding to find the best alignment between the text and audio), we select the portion yn of the waveform corresponding to xn.”
- Models of Visually Grounded Speech Signal Pay Attention to Nouns: A Bilingual Experiment on English and Japanese (2019, unknown): “behaviour of the same architecture on two typologically different languages. We forced aligned each spoken caption to its transcription (using the Montreal Forced Aligner [18] and Maus Forced Aligner [19] for English and Japanese respectively), resulting in alignments at word and phone level. We als”
- MaSS: A Large and Clean Multilingual Corpus of Sentence-aligned Spoken Utterances Extracted from the Bible (2019, methodology): “For each chapter, we extracted speech-to-text alignments through the Maus forced aligner(8) [25] online platform.”
- Cortical encoding of probabilistic temporal predictions during speech perception (2026, unknown): “- Linguistic onsets: Onset times of words, syllables, and phonemes, estimated using the BAS web service (80).”
- Phonological acquisition depends on the timing of speech sounds: Deconvolution EEG modeling across the first five years (2023, unknown): “Phonological annotations (see Table 1) were obtained via forced alignment of orthographic transcript to the acoustic waveform using the WEBMAUS automatic segmentation tool ( 51 , 52 ).”