About

Megha Sundara is a Professor in the Department of Linguistics at UCLA and serves as the Department Chair. She earned her Ph.D. in 2005 from McGill University. Her research focuses on various aspects of language development, phonetics, phonology, and speech perception, with particular attention to infant language acquisition, phonotactics, morphological segmentation, and prosody. Her work integrates experimental studies, computational modeling, and cross-linguistic analyses to understand how infants and children acquire and process language, as well as how perceptual and production mechanisms develop over time. Throughout her career, Sundara has made significant contributions to the understanding of early language development, including infants' sensitivity to phonotactic cues, morphological structures, and prosodic features. Her research has explored how bilingual infants segment words, how infants discriminate subtle phonetic contrasts, and how exposure to different languages influences speech perception and production. She has also investigated the perceptual and production links in speech development, as well as the effects of language experience on phonological and lexical processing. Her work is widely published in leading journals and presented at international conferences, establishing her as a prominent figure in the field of language acquisition and phonetics.

Research topics

• Sociology
• Psychology
• Linguistics
• Developmental psychology
• Natural Language Processing
• Computer Science
• Mathematics
• Communication
• Artificial Intelligence
• Speech recognition
• Statistics
• Cognitive psychology

Selected publications

• Data

  OSF Preprints (OSF Preprints) · 2026-02-25

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• Annotation criteria & spectrograms

  OSF Preprints (OSF Preprints) · 2026-02-25

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• The acquisition of native language phonotactics: Integrating insights from machine learning, and adult and infant experiments

  Cognition · 2026-03-15

  articleOpen access1st authorCorresponding

  Languages differ in their phonotactics - the restrictions on positions and sequencing of segments. Many phonotactic restrictions are specific to a given language, and therefore must be learned from the input infants receive. First, we used data from adult experiments to identify maximally contrastive segmental regularities in English. Then, in three infant experiments, we showed that sensitivity to segmental regularities is induced by 5 months of age in English-learning infants. Finally, using methods from machine learning we evaluated two competing hypotheses about how infants learn phonotactics against the findings from the infant experiments. Our results show that 5-month-olds could not learn segmental restrictions from either unsegmented utterances or from words they associate with referents. We discuss the implication of these results for the mechanisms involved in phonotactic acquisition.

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• Supplementary materials for "The acquisition of native language phonotactics: Integrating insights from machine learning, and adult and infant experiments"

  OSF Preprints (OSF Preprints) · 2026-03-03

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• Does perceptual learning for segmental phonotactics generalize across talkers?

  OSF Preprints (OSF Preprints) · 2026-01-28

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• NE Speakers

  OSF Preprints (OSF Preprints) · 2026-02-25

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• Scripts

  OSF Preprints (OSF Preprints) · 2026-02-25

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• Miscellaneous stats

  OSF Preprints (OSF Preprints) · 2026-02-25

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• Phonological Choices Drive F0 Range Expansion and Lengthening in Bengali and English Infant-Directed Speech

  Languages · 2026-04-01

  articleOpen accessSenior author

  This study builds on a small body of work, all on Japanese, demonstrating how intonational phonology is critical for understanding prosodic modifications in infant-directed speech (IDS) relative to adult-directed speech. We performed similar analyses on simulated infant-directed speech vs. reading of a story in English and Bengali: two languages that – unlike Japanese – both have stress and do not use fundamental frequency (F0) to signal changes in word-level meaning, but that have two very different intonational grammars. These differences allowed us to disentangle previous hypotheses about intonational exaggeration in IDS being concentrated in a particular part of the melody. We tested hypotheses that state this locus of exaggeration is either at: the final position in the melody (final in the intonational phrase), the most unpredictable part of the melody, or in pragmatically informative tones. Our results support the first hypothesis. We found that the phonological choices of speakers to chunk the story into shorter, larger prosodic constituents drive intonational exaggeration in IDS. This is because the intonational phrase-final position in both languages is the site of greatest pre-boundary lengthening and F0 range expansion. We also demonstrate: (i) quantification of predictability in intonational melodies using probabilistic finite state automaton representations of intonational grammars and (ii) F0 statistical analyses that are robust and scalable to large, naturalistic IDS corpora.

  PublisherOA PDFDOI

• Reassessing the labial-coronal asymmetry in infants’ discrimination of medial consonants

  HAL (Le Centre pour la Communication Scientifique Directe) · 2026-02-04

  articleOpen accessSenior author

  Asymmetric speech sound discrimination has been observed in both adults and infants. Here we focus on the labial-coronal asymmetry documented in Dutch- and Japanese-learning infants, who success-fully discriminate between /ɔmpa/ and /ɔnta/ only after habituation to /ɔmpa / (Tsuji et al., 2015). We hypothesized that this asymmetry is due to the inherent greater intensity of coronal compared to labial stop consonants. However, testing 64 French- and English-learning five-month-olds with Tsuji et al.’s stimuli, we observed successful discrimination regardless of language and of habituation condition, with only a numeric asymmetry in the predicted direction, i.e. a numerically larger looking time dif-ference between switch and same trials after habituation to /ɔmpa/ than to /ɔnta/. So, we propose alter-native ways to test our hypothesis in future research.

  PublisherOA PDFDOI

Recent grants

• Development of Native Language Preference: Behavioral and Physiological Indices

  NSF · $403k · 2010–2015

• A new approach to computational model evaluation: Benchmarking against infant experimental data

  NSF · $550k · 2022–2026

• Morphological acquisition in early infancy: Experimental and computational studies

  NSF · $450k · 2020–2024

Frequent coauthors

• Linda Polka

  Centre for Research on Brain Language and Music

  20 shared

• Robert Chen

  IFC Research (United Kingdom)

  17 shared

• Aravind Kumar Namasivayam

  University of Toronto

  16 shared

• Thierry Nazzi

  12 shared

• Katherine Demuth

  Macquarie University

  10 shared

• Jae Yung Song

  University of Wisconsin–Milwaukee

  9 shared

• Patricia K. Kuhl

  University of Washington

  8 shared

• Judit Gervain

  8 shared