all AI news
DDKtor: Automatic Diadochokinetic Speech Analysis. (arXiv:2206.14639v1 [eess.AS])
June 30, 2022, 1:10 a.m. | Yael Segal, Kasia Hitczenko, Matthew Goldrick, Adam Buchwald, Angela Roberts, Joseph Keshet
cs.LG updates on arXiv.org arxiv.org
Diadochokinetic speech tasks (DDK), in which participants repeatedly produce
syllables, are commonly used as part of the assessment of speech motor
impairments. These studies rely on manual analyses that are time-intensive,
subjective, and provide only a coarse-grained picture of speech. This paper
presents two deep neural network models that automatically segment consonants
and vowels from unannotated, untranscribed speech. Both models work on the raw
waveform and use convolutional layers for feature extraction. The first model
is based on an LSTM …
More from arxiv.org / cs.LG updates on arXiv.org
Testing the Segment Anything Model on radiology data
2 days, 7 hours ago |
arxiv.org
Calorimeter shower superresolution
2 days, 8 hours ago |
arxiv.org
Jobs in AI, ML, Big Data
Software Engineer for AI Training Data (School Specific)
@ G2i Inc | Remote
Software Engineer for AI Training Data (Python)
@ G2i Inc | Remote
Software Engineer for AI Training Data (Tier 2)
@ G2i Inc | Remote
Data Engineer
@ Lemon.io | Remote: Europe, LATAM, Canada, UK, Asia, Oceania
Artificial Intelligence – Bioinformatic Expert
@ University of Texas Medical Branch | Galveston, TX
Lead Developer (AI)
@ Cere Network | San Francisco, US