Mark Hasegawa-Johnson
researcher
Facts
7 properties- Instance of
- human
- Occupation
- researcher
- Family name
- Hasegawa-Johnson[4]
- Maintained by WikiProject
- WikiProject Mathematics[6]
🏷️ Also known as
en Mark Hasegawa-Johnson
ja マーク・ハセガワ・ジョンソン
nl M Hasegawa-Johnson
🔖 Identifiers · 10
- ORCID iD
- 0000-0002-5631-2893
- Image (Wikimedia Commons)
- Mark Hasegawa-Johnson at AAAS 2025 02.jpg ↗
- Academic Tree ID
- 344939
- DBLP author ID
- 70/3186
- Google Knowledge Graph ID
- /g/11dxpwxkwt
- Google Scholar author ID
- 18O0OAwAAAAJ
- IMDb ID
- nm2557673
- LinkedIn personal profile ID
- mark-hasegawa-johnson-21a86825
- ResearchGate profile ID
- Mark-Hasegawa-Johnson
- ZbMATH author ID
- hasegawa-johnson.mark
🔗 Connections
Author of 45
Acquiring Speech Transcriptions Using Mismatched Crowdsourcing,
Adapting ASR for under-resourced languages using mismatched transcriptions,
A DNN-HMM-DNN Hybrid Model for Discovering Word-Like Units from Spoken Captions and Image Regions,
Align or attend? Toward More Efficient and Accurate Spoken Word Discovery Using Speech-to-Image Retrieval,
Analysis of acoustic and voice quality features for the classification of infant and mother vocalizations,
ASR for Under-Resourced Languages From Probabilistic Transcription,
Automated morphological phenotyping using learned shape descriptors and functional maps: A novel approach to geometric morphometrics,
Automatic Speech Recognition Using Probabilistic Transcriptions in Swahili, Amharic, and Dinka
+37 more
← Authored by 45
Acquiring Speech Transcriptions Using Mismatched Crowdsourcing,
Adapting ASR for under-resourced languages using mismatched transcriptions,
A DNN-HMM-DNN Hybrid Model for Discovering Word-Like Units from Spoken Captions and Image Regions,
Align or attend? Toward More Efficient and Accurate Spoken Word Discovery Using Speech-to-Image Retrieval,
Analysis of acoustic and voice quality features for the classification of infant and mother vocalizations,
ASR for Under-Resourced Languages From Probabilistic Transcription,
Automated morphological phenotyping using learned shape descriptors and functional maps: A novel approach to geometric morphometrics,
Automatic Speech Recognition Using Probabilistic Transcriptions in Swahili, Amharic, and Dinka
+37 more
Affiliated with 3
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