Papers by Alexis Michaud
Establishing degrees of closeness between audio recordings along different dimensions using large-scale cross-lingual models (2024.findings-eacl)
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| Challenge: | Existing methods to analyze speech representations using pretraining data are difficult to achieve for endangered languages. |
| Approach: | They propose an unsupervised method to examine the level of abstraction in vector representations of speech from a pretrained model to determine their level of abstractness. |
| Outcome: | The proposed method is fully unsupervised and could be used in comparative studies on under-documented languages. |
Evaluation Phonemic Transcription of Low-Resource Tonal Languages for Language Documentation (L18-1)
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| Challenge: | Language documentation involves recording the speech of native speakers. |
| Approach: | They propose to use a neural network architecture to model phonemes and tones versus modelling them separately. |
| Outcome: | The proposed method improves efficiency, minimizes typographical errors and maintains transcription faithfulness to acoustic signal while highlighting phonetic and phonemic facts for linguistic consideration. |
AlloVera: A Multilingual Allophone Database (2020.lrec-1)
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David R. Mortensen, Xinjian Li, Patrick Littell, Alexis Michaud, Shruti Rijhwani, Antonios Anastasopoulos, Alan W Black, Florian Metze, Graham Neubig
| Challenge: | Phonemes are contrastive phonological units, and allophones are their various concrete realizations. |
| Approach: | They propose a resource that maps allophones to phonemes for 14 languages . they propose phonological representations that are much closer to a universal transcription . |
| Outcome: | The proposed resource maps from 218 allophones to phonemes for 14 languages. |