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Skip to Search Results- 3forced alignment
- 2audio segmentation
- 2speech recognition
- 1acoustics
- 1acoutic phonetics
- 1automatic speech recognition
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2018-01-01
Matthew C. Kelley, Benjamin V. Tucker
The present paper investigates the effect of different inputs on the accuracy of a forced alignment tool built using deep neural networks. Both raw audio samples and Mel-frequency cepstral coefficients were compared as network inputs. A set of experiments were performed using the TIMIT speech...
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2018-01-01
Matthew C. Kelley, Benjamin V. Tucker
Poster for the paper "A comparison of input types to a deep neural network-based forced aligner," presented at Interspeech 2018. Typo in alignment matrix (O[2,2] referenced O[1,2] instead of O[1,1]) updated on June 4, 2019. PAPER ABSTRACT: The present paper investigates the effect of different...
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2021-12-03
Matthew C. Kelley, Scott James Perry, Benjamin V. Tucker
Forced alignment is increasingly used in phonetics to automatically produce boundaries between words and phones. These boundaries can have significant errors and are often only placed at some predetermined time interval, like every 10 ms. We discuss some potential remedies to these difficulties...