Search Results for author:
Found 9 papers, 8 papers with code
BabySLM: language-acquisition-friendly benchmark of self-supervised spoken language models
Self-supervised techniques for learning speech representations have been shown to develop linguistic competence from exposure to speech without the need for human labels.
Analysing the Impact of Audio Quality on the Use of Naturalistic Long-Form Recordings for Infant-Directed Speech Research
Our results show that the use of modest and high audio quality naturalistic speech data result in largely similar conclusions on IDS and ADS in terms of acoustic analyses and modelling experiments.
Brouhaha: multi-task training for voice activity detection, speech-to-noise ratio, and C50 room acoustics estimation
Most automatic speech processing systems register degraded performance when applied to noisy or reverberant speech.
ZR-2021VG: Zero-Resource Speech Challenge, Visually-Grounded Language Modelling track, 2021 edition
We present the visually-grounded language modelling track that was introduced in the Zero-Resource Speech challenge, 2021 edition, 2nd round.
An open-source voice type classifier for child-centered daylong recordings
Spontaneous conversations in real-world settings such as those found in child-centered recordings have been shown to be amongst the most challenging audio files to process.
Seshat: A tool for managing and verifying annotation campaigns of audio data
We introduce Seshat, a new, simple and open-source software to efficiently manage annotations of speech corpora.
Speaker detection in the wild: Lessons learned from JSALT 2019
This paper presents the problems and solutions addressed at the JSALT workshop when using a single microphone for speaker detection in adverse scenarios.
Audio and Speech Processing Sound
The Second DIHARD Diarization Challenge: Dataset, task, and baselines
This paper introduces the second DIHARD challenge, the second in a series of speaker diarization challenges intended to improve the robustness of diarization systems to variation in recording equipment, noise conditions, and conversational domain.
Are words easier to learn from infant- than adult-directed speech? A quantitative corpus-based investigation
At the acoustic level we show that, as has been documented before for phonemes, the realizations of words are more variable and less discriminable in IDS than in ADS.
