20 citations · 74 across the 21 of their papers we have counts for
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Benchmarking Adult Addressee Classification Across Child- and Adult-Directed Speech Datasets
Sofoklis Kakouros, Daniil Kocharov, Okko Räsänen
In this work, we present a comprehensive analysis of classification performance for distinguishing child-directed speech (CDS) from adult-directed speech (ADS) using speech data fr…
Deriving Benchmarking Datasets from Long-Form Recordings: Challenges and Opportunities
Kaveri K. Sheth, Lawrence Borst, Tarek Kunze +6
Long-form recordings (LFRs) of child-centered audio are ecologically valid sources for studying early language development, but three problems limit their use. First, LFR corpora a…
A model of early word acquisition based on realistic-scale audiovisual naming events
Khazar Khorrami, Okko Räsänen
Infants gradually learn to parse continuous speech into words and connect names with objects, yet the mechanisms behind development of early word perception skills remain unknown.…
Simultaneous or Sequential Training? How Speech Representations Cooperate in a Multi-Task Self-Supervised Learning System
Khazar Khorrami, María Andrea Cruz Blandón, Tuomas Virtanen +1
Speech representation learning with self-supervised algorithms has resulted in notable performance boosts in many downstream tasks. Recent work combined self-supervised learning (S…
Crowdsourcing and Evaluating Text-Based Audio Retrieval Relevances
Huang Xie, Khazar Khorrami, Okko Räsänen +1
This paper explores grading text-based audio retrieval relevances with crowdsourcing assessments. Given a free-form text (e.g., a caption) as a query, crowdworkers are asked to gra…
On Negative Sampling for Contrastive Audio-Text Retrieval
Huang Xie, Okko Räsänen, Tuomas Virtanen
This paper investigates negative sampling for contrastive learning in the context of audio-text retrieval. The strategy for negative sampling refers to selecting negatives (either…
Unsupervised Audio-Caption Aligning Learns Correspondences between Individual Sound Events and Textual Phrases
Huang Xie, Okko Räsänen, Konstantinos Drossos +1
We investigate unsupervised learning of correspondences between sound events and textual phrases through aligning audio clips with textual captions describing the content of a whol…
Can phones, syllables, and words emerge as side-products of cross-situational audiovisual learning? -- A computational investigation
Khazar Khorrami, Okko Räsänen
Decades of research has studied how language learning infants learn to discriminate speech sounds, segment words, and associate words with their meanings. While gradual development…
Language-Independent Approach for Automatic Computation of Vowel Articulation Features in Dysarthric Speech Assessment
Yuanyuan Liu, Nelly Penttilä, Tiina Ihalainen +3
Imprecise vowel articulation can be observed in people with Parkinson's disease (PD). Acoustic features measuring vowel articulation have been demonstrated to be effective indicato…
Automatic Analysis of the Emotional Content of Speech in Daylong Child-Centered Recordings from a Neonatal Intensive Care Unit
Einari Vaaras, Sari Ahlqvist-Björkroth, Konstantinos Drossos +1
Researchers have recently started to study how the emotional speech heard by young infants can affect their developmental outcomes. As a part of this research, hundreds of hours of…
Unsupervised Discovery of Recurring Speech Patterns Using Probabilistic Adaptive Metrics
Okko Räsänen, María Andrea Cruz Blandón
Unsupervised spoken term discovery (UTD) aims at finding recurring segments of speech from a corpus of acoustic speech data. One potential approach to this problem is to use dynami…