Toward a model for lexical access based on acoustic landmarks and distinctive features.

By Kenneth N. Stevens. Journal of the Acoustical Society of America, 2002

589 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Experimental and Cognitive Psychology, Signal Processing

View Paper: https://www.semanticscholar.org/paper/8f0da8dd0dec86f20d6879d86392935ff81240e8

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Citations in the corpus

How are words stored in memory? Beyond phones and phonemes (2007, background): “…''linguistically relevant cues'') and others that are minor enough to be ignored or backgrounded (Blumstein & Stevens, 1979; Chomsky & Halle, 1968; Stevens, 2000; Stevens, Keyser, & Kawasaki, 1986), most observers find no basis for treating some acoustic features as ''distinctive'' (that is,…”
Computational neuroanatomy of speech production (2012, background): “However, the idea that the basic unit of speech perception is larger than the phoneme has met with resistance, as is evident from the fact that the dominant models of speech recognition include a phoneme-level component 129,137,138 .”
Eight questions about spoken-word recognition (2007, background): “…prelexical level, about whether the processes operating there are speech specific, about the role of visual cues in speech processing, and even about whether there is a prelexical level (see Pisoni, this volume, Massaro, this volume, Stevens, 2002, and Diehl et al., 2004, for further discussion).”
Structured speech modeling (2006, unknown): “, [3], [6], [9], [29], [34], [40], [42], [49], [53], [59]).”
Acoustic landmarks drive delta-theta oscillations to enable speech comprehension by facilitating perceptual parsing (2013, unknown): “See Stevens (2002). Stimuli”
The Encoding of Speech Sounds in the Superior Temporal Gyrus (2019, background): “Based on long-standing theories that have postulated that amplitude events signal key temporal landmarks for spectral analysis of the speech signal (Chistovich and Lublinskaya, 1979; Stevens, 2002), we suggest that the amplitude envelope may be encoded as a discrete landmark feature.”
Exploring how deep neural networks form phonemic categories (2015, methodology): “Within these subcategories, the nodes are organized primarily by manner of articulation, resembling the feature hierarchy described by Stevens [14].”
Dorsal and ventral streams: a framework for understanding aspects of the functional anatomy of language. (2004, background): “This process is likely a multistage operation: for example, Stevens (2002) postulates multiple steps just in the derivation from the acoustic speech signal to a representation of a sequence of segments.”
The cortical organization of speech processing (2007, background): “Although the presupposition typically remains unstated, previous models have assumed that either hierarchical processing (a segmental analysis followed by syllable construction on the basis of smaller units”
Dynamic Speech Models: Theory, Algorithms, and Applications (2006, background): “These properties are especially useful for detecting certain special speech events and for identifying temporal “landmarks” as a prerequisite for estimating the phonological features relevant to consonants [2, 3].”
The human auditory cortex concurrently tracks syllabic and phonemic timescales via acoustic spectral flux (2024, unknown): “Short-timescale dynamics ( ~ 20 to 80 ms) bear information about the local spectro-temporal structure of speech units and their transitions ( 2 , 4 , 5 , 36 – 39 ).”
Unified Coding of Spectral and Temporal Phonetic Cues: Electrophysiological Evidence for Abstract Phonological Features (2021, background): “…of language processing that posit that speech sounds are stored in terms of featural representations and that these features are utilized during on-line spoken word recognition (Hickok, 2014; Poeppel & Monahan, 2011; Gow, 2003; Stevens, 2002; McClelland & Elman, 1986; Halle & Stevens, 1962).”