12.2 Speech recognition

Speech recognition is a crucial aspect of psycholinguistics, focusing on how we perceive and interpret spoken language. It involves complex processes that integrate sensory input with linguistic knowledge, providing insights into language comprehension and cognitive processing.

Understanding speech recognition helps explain how humans rapidly perceive speech in various contexts. It involves bottom-up and top-down processing, context-based interpretation, and lexical access. Challenges include variability in speech production, continuous speech segmentation, and background noise effects.

Basics of speech recognition

• Speech recognition forms a fundamental aspect of psycholinguistics, focusing on how humans perceive and interpret spoken language
• Understanding speech recognition processes provides insights into language comprehension, cognitive processing, and communication disorders

Components of speech sounds

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• Vowels produced by unobstructed airflow through the vocal tract, characterized by formant frequencies
• Consonants formed by various types of constrictions in the vocal tract (stops, fricatives, nasals)
• Suprasegmental features include pitch, stress, and intonation patterns
• Coarticulation effects occur as adjacent sounds influence each other's production

Acoustic features of speech

• Fundamental frequency (F0) determines the perceived pitch of speech
• Formants represent resonant frequencies of the vocal tract, crucial for vowel identification
• Voice onset time (VOT) distinguishes between voiced and voiceless consonants
• Spectral cues provide information about manner and place of articulation

Phonemes vs allophones

• Phonemes function as abstract units of sound that distinguish meaning in a language
• Allophones represent variant pronunciations of a phoneme in different contexts
• Complementary distribution occurs when allophones appear in mutually exclusive environments
• Free variation allows multiple allophones to occur in the same phonetic context without changing meaning

Cognitive processes in recognition

• Speech recognition involves complex cognitive processes that integrate sensory input with linguistic knowledge
• Understanding these processes helps explain how humans can rapidly and accurately perceive speech in various contexts

Bottom-up vs top-down processing

• Bottom-up processing analyzes acoustic input to build larger linguistic units
• Top-down processing uses contextual information and expectations to guide interpretation
• Interactive models propose a combination of both processes for efficient speech recognition
• Predictive coding suggests the brain generates predictions to facilitate faster processing

Role of context in perception

• Semantic context influences word recognition and disambiguation
• Syntactic context aids in predicting upcoming words and structures
• Pragmatic context shapes interpretation based on situational factors
• Phonological neighborhood effects impact word recognition speed and accuracy

Lexical access and retrieval

• Mental lexicon stores words and their associated information
• Spreading activation theory explains how related concepts are activated during recognition
• Frequency effects show that common words are recognized faster than rare words
• Priming facilitates recognition of related words through pre-activation

Challenges in speech recognition

• Speech recognition faces numerous challenges due to the complexity and variability of human speech
• Understanding these challenges is crucial for developing effective speech recognition systems and therapies

Variability in speech production

• Speaker differences in accent, dialect, and vocal tract characteristics
• Emotional state and speaking rate affect acoustic properties of speech
• Coarticulation effects cause phonemes to be pronounced differently based on surrounding sounds
• Sociolinguistic factors influence speech patterns across different groups

Continuous speech segmentation

• Lack of clear word boundaries in fluent speech poses a challenge for recognition
• Prosodic cues (stress, intonation) aid in identifying word and phrase boundaries
• Statistical learning helps listeners identify recurring patterns in speech
• Language-specific phonotactic constraints guide segmentation strategies

Effects of background noise

• Signal-to-noise ratio impacts speech intelligibility in noisy environments
• Cocktail party effect demonstrates the ability to focus on a single speaker among multiple voices
• Energetic masking occurs when noise physically obscures speech signals
• Informational masking involves cognitive interference from meaningful background sounds

Models of speech recognition

• Speech recognition models attempt to explain how humans process and understand spoken language
• These models provide frameworks for research and inform the development of speech recognition technologies

TRACE model

• Interactive activation model with bidirectional processing
• Three levels of processing phonetic features, phonemes, and words
• Lateral inhibition between competing units at each level
• Accounts for context effects and top-down influences on perception

Cohort model

• Word recognition begins with activation of all words sharing initial sounds (cohort)
• Progressive elimination of candidates as more acoustic information becomes available
• Explains the importance of word onsets in recognition
• Incorporates frequency effects and contextual constraints

Shortlist model

• Two-stage model combining bottom-up activation with competition
• Initial stage generates a shortlist of word candidates based on acoustic input
• Second stage involves competition between candidates for best match
• Accounts for continuous speech recognition and segmentation

Neurological basis

• Understanding the neural substrates of speech recognition provides insights into language processing and disorders
• Neuroimaging and lesion studies have revealed key brain regions involved in speech perception

Brain regions for speech processing

• Primary auditory cortex (Heschl's gyrus) processes basic acoustic features
• Superior temporal gyrus involved in phonemic and word-level processing
• Broca's area contributes to articulatory and syntactic processing
• Wernicke's area crucial for semantic processing and comprehension

Temporal processing of speech

• Millisecond-level precision required for distinguishing rapid acoustic changes
• Temporal integration windows for different linguistic units (phonemes, syllables, words)
• Neural oscillations synchronize with speech rhythms to facilitate processing
• Temporal processing deficits linked to various language disorders

Hemispheric specialization

• Left hemisphere dominance for language processing in most individuals
• Right hemisphere contributes to prosodic and emotional aspects of speech
• Bilateral activation observed for complex language tasks
• Plasticity allows for reorganization in cases of brain injury or developmental differences

Individual differences

• Speech recognition abilities vary across individuals due to various factors
• Understanding these differences is crucial for tailoring interventions and technologies to diverse populations

Age-related changes in recognition

• Presbycusis (age-related hearing loss) affects high-frequency hearing
• Cognitive decline impacts working memory and processing speed for speech
• Compensatory mechanisms develop to maintain comprehension in older adults
• Neuroplasticity allows for adaptation to age-related changes in speech processing

Bilingualism and speech perception

• Bilingual advantage in certain aspects of speech perception (phoneme discrimination)
• Language switching and control mechanisms influence speech processing
• Cross-linguistic transfer affects perception of non-native speech sounds
• Age of acquisition impacts neural organization for multiple languages

Hearing impairments and recognition

• Cochlear implants provide auditory input for severe to profound hearing loss
• Auditory training improves speech recognition in hearing-impaired individuals
• Speechreading (lip-reading) supplements auditory information for comprehension
• Assistive technologies (hearing aids, FM systems) enhance speech recognition in various environments

Technology and applications

• Speech recognition technology has advanced rapidly, with numerous practical applications
• Understanding human speech recognition informs the development of more effective and natural speech interfaces

Automatic speech recognition systems

• Hidden Markov Models (HMMs) model temporal patterns in speech
• Deep Neural Networks improve recognition accuracy and robustness
• Feature extraction techniques (MFCC, PLP) convert acoustic signals to meaningful representations
• Language models incorporate contextual information to improve recognition

Voice assistants and AI

• Natural language processing enables understanding of user intent
• Dialogue management systems maintain context across multiple interactions
• Text-to-speech synthesis provides natural-sounding responses
• Personalization adapts to individual user preferences and speech patterns

Speech recognition in forensics

• Speaker identification uses acoustic features to match voices to individuals
• Forensic phonetics analyzes speech patterns for legal investigations
• Voice stress analysis attempts to detect deception through vocal characteristics
• Challenges include disguised voices and variability in recording conditions

Cross-linguistic considerations

• Speech recognition processes vary across languages due to different phonological systems
• Understanding these differences is crucial for developing multilingual speech technologies and theories

Tonal vs non-tonal languages

• Tonal languages use pitch contours to distinguish lexical meaning
• Non-tonal languages use pitch primarily for prosodic functions
• Perceptual cue weighting differs between speakers of tonal and non-tonal languages
• Tone sandhi phenomena in tonal languages affect speech recognition processes

Phonotactic constraints across languages

• Language-specific rules govern permissible sound combinations
• Phonotactic probability influences word recognition and segmentation
• Cross-linguistic transfer of phonotactic knowledge in second language learning
• Universal phonotactic preferences (CV syllables) observed across languages

Universal vs language-specific features

• Categorical perception of phonemes observed across languages
• Language-specific phoneme inventories shape perceptual boundaries
• Prosodic features (stress, intonation) vary in their linguistic functions
• Statistical learning mechanisms appear universal but tuned to specific language input

Development of speech recognition

• Speech recognition abilities develop rapidly in early childhood
• Understanding this process informs theories of language acquisition and interventions for developmental disorders

Infant speech perception

• Newborns show preference for speech sounds over non-speech
• Categorical perception of phonemes present from early infancy
• Statistical learning allows infants to extract patterns from continuous speech
• Preference for infant-directed speech (motherese) facilitates language learning

Critical period for language acquisition

• Sensitive period for optimal language acquisition in early childhood
• Decline in ability to acquire native-like phonology after puberty
• Neural plasticity allows for reorganization of language networks during critical period
• Second language acquisition affected by age of exposure and learning context

Perceptual narrowing in infancy

• Initial ability to discriminate all speech sounds narrows to language-specific contrasts
• Decline in non-native phoneme discrimination around 6-12 months
• Maintenance of sensitivity to native language contrasts
• Bilingual infants maintain broader perceptual abilities for longer periods

Disorders and impairments

• Various disorders can affect speech recognition abilities
• Understanding these impairments helps in developing targeted interventions and assistive technologies

Specific language impairment

• Difficulties in language acquisition and processing without other cognitive deficits
• Challenges in phonological processing and working memory
• Impaired ability to use grammatical cues for word recognition
• Interventions focus on improving phonological awareness and language skills

Dyslexia and speech processing

• Difficulties in reading often accompanied by subtle speech processing deficits
• Impaired phonological awareness and rapid auditory processing
• Challenges in perceiving speech in noise and processing temporal cues
• Interventions target phonological skills and auditory training

Aphasia and recognition deficits

• Language impairment resulting from brain damage (stroke, injury)
• Wernicke's aphasia associated with impaired speech comprehension
• Conduction aphasia affects repetition and phonological processing
• Recovery and rehabilitation depend on lesion location and extent of damage