Acoustic-Emergent Phonology in the Amplitude Envelope of Child-Directed Speech

Abstract

When acquiring language, young children may use acoustic spectro-temporal patterns in speech to derive phonological units in spoken language (e.g., prosodic stress patterns, syllables, phonemes). Children appear to learn acoustic-phonological mappings rapidly, without direct instruction, yet the underlying developmental mechanisms remain unclear. Across different languages, a relationship between amplitude envelope sensitivity and phonological development has been found, suggesting that children may make use of amplitude modulation (AM) patterns within the envelope to develop a phonological system. Here we present the Spectral Amplitude Modulation Phase Hierarchy (S-AMPH) model, a set of algorithms for deriving the dominant AM patterns in child-directed speech (CDS). Using Principal Components Analysis, we show that rhythmic CDS contains an AM hierarchy comprising 3 core modulation timescales. These timescales correspond to key phonological units: prosodic stress (Stress AM, ~2 Hz), syllables (Syllable AM, ~5 Hz) and onset-rime units (Phoneme AM, ~20 Hz). We argue that these AM patterns could in principle be used by naïve listeners to compute acoustic-phonological mappings without lexical knowledge. We then demonstrate that the modulation statistics within this AM hierarchy indeed parse the speech signal into a primitive hierarchically-organised phonological system comprising stress feet (proto-words), syllables and onset-rime units. We apply the S-AMPH model to two other CDS corpora, one spontaneous and one deliberately-timed. The model accurately identified 72–82% (freely-read CDS) and 90–98% (rhythmically-regular CDS) stress patterns, syllables and onset-rime units. This in-principle demonstration that primitive phonology can be extracted from speech AMs is termed Acoustic-Emergent Phonology (AEP) theory. AEP theory provides a set of methods for examining how early phonological development is shaped by the temporal modulation structure of speech across languages. The S-AMPH model reveals a crucial developmental role for stress feet (AMs ~2 Hz). Stress feet underpin different linguistic rhythm typologies, and speech rhythm underpins language acquisition by infants in all languages.

Neural encoding of the speech envelope by children with developmental dyslexia

“…Further, recent analyses of the amplitude modulation structure of Australian English infant-directed speech (IDS) show a modulation peak at 2 Hz, the “prosodic rate” (see Leong, Kalashnikova, Burnham, & Goswami, 2014), not at 4–6 Hz, the modulation peak found for adult-directed speech (ADS, see Greenberg, Carvey, Hitchcock, & Chang, 2003). These different modulation peaks imply that early in development, accurate encoding of low frequency envelopes (delta band) could play a crucial role in setting up a phonological lexicon (Leong & Goswami, 2015). Infants and young children who are relatively insensitive to low-frequency envelope information would benefit less from the prosodic information in IDS as they build their lexical phonological representations.…”

Probabilistic Amplitude Demodulation Features in Speech Synthesis for Improving Prosody

“…Nonetheless, it remains unclear which modulations (time-scales), are the most important relating acoustic information with phonological. Investigating this issue, Leong and Goswami [15], studied how acoustic spectrotemporal structure is related to the linguistic phonological structure of speech, using amplitude demodulation in three time-scales, i.e, prosodic stress, syllable and onset-rime unit (phonemes) levels.…”

Speech Impairments in Intellectual Disability: An Acoustic Study

“…The spectro-temporal features [28][29][30][31][32][33] at these timescales highly correlated speech intelligibly and ability to understand or comprehend. Studies reported impairments in short time scales [34][35][36] and long time scales [37,38,40] on the speech signal of children with neurodevelopmental disorders. Most of these studies focused on the impairments in the spectro-temporal features in the speech of subjects with intellectual disabilities but none has developed the classification model for these groups based on features encoded at multiple timescales.…”