Language identification with suprasegmental cues: A study based on speech resynthesis

This paper proposes a new experimental paradigm to explore the discriminability of languages, a question which is crucial to the child born in a bilingual environment. This paradigm employs the speech resynthesis technique, enabling the experimenter to preserve or degrade acoustic cues such as phonotactics, syllabic rhythm or intonation from natural utterances. English and Japanese sentences were resynthesized, preserving broad phonotactics, rhythm and intonation (Condition 1), rhythm and intonation (Condition 2), intonation only (Condition 3), or rhythm only (Condition 4). The findings support the notion that syllabic rhythm is a necessary and sufficient cue for French adult subjects to discriminate English from Japanese sentences. The results are consistent with previous research using low-pass filtered speech, as well as with phonological theories predicting rhythmic differences between languages. Thus, the new methodology proposed appears to be well-suited to study language discrimination. Applications for other domains of psycholinguistic research and for automatic language identification are considered

Severity Classification of Parkinson's Disease from Speech using Single Frequency Filtering-based Features

Developing objective methods for assessing the severity of Parkinson's disease (PD) is crucial for improving the diagnosis and treatment. This study proposes two sets of novel features derived from the single frequency filtering (SFF) method: (1) SFF cepstral coefficients (SFFCC) and (2) MFCCs from the SFF (MFCC-SFF) for the severity classification of PD. Prior studies have demonstrated that SFF offers greater spectro-temporal resolution compared to the short-time Fourier transform. The study uses the PC-GITA database, which includes speech of PD patients and healthy controls produced in three speaking tasks (vowels, sentences, text reading). Experiments using the SVM classifier revealed that the proposed features outperformed the conventional MFCCs in all three speaking tasks. The proposed SFFCC and MFCC-SFF features gave a relative improvement of 5.8% and 2.3% for the vowel task, 7.0% & 1.8% for the sentence task, and 2.4% and 1.1% for the read text task, in comparison to MFCC features.Comment: Accepted by INTERSPEECH 202

A robust speech enhancement method in noisy environments

Speech enhancement aims to eliminate or reduce undesirable noises and distortions, this processing should keep features of the speech to enhance the quality and intelligibility of degraded speech signals. In this study, we investigated a combined approach using single-frequency filtering (SFF) and a modified spectral subtraction method to enhance single-channel speech. The SFF method involves dividing the speech signal into uniform subband envelopes, and then performing spectral over-subtraction on each envelope. A smoothing parameter, determined by the a-posteriori signal-to-noise ratio (SNR), is used to estimate and update the noise without the need for explicitly detecting silence. To evaluate the performance of our algorithm, we employed objective measures such as segmental SNR (segSNR), extended short-term objective intelligibility (ESTOI), and perceptual evaluation of speech quality (PESQ). We tested our algorithm with various types of noise at different SNR levels and achieved results ranging from 4.24 to 15.41 for segSNR, 0.57 to 0.97 for ESTOI, and 2.18 to 4.45 for PESQ. Compared to other standard and existing speech enhancement methods, our algorithm produces better results and performs well in reducing undesirable noises

Classification and Separation Techniques based on Fundamental Frequency for Speech Enhancement

[ES] En esta tesis se desarrollan nuevos algoritmos de clasificación y mejora de voz basados en las propiedades de la frecuencia fundamental (F0) de la señal vocal. Estas propiedades permiten su discriminación respecto al resto de señales de la escena acústica, ya sea mediante la definición de características (para clasificación) o la definición de modelos de señal (para separación). Tres contribuciones se aportan en esta tesis: 1) un algoritmo de clasificación de entorno acústico basado en F0 para audífonos digitales, capaz de clasificar la señal en las clases voz y no-voz; 2) un algoritmo de detección de voz sonora basado en la aperiodicidad, capaz de funcionar en ruido no estacionario y con aplicación a mejora de voz; 3) un algoritmo de separación de voz y ruido basado en descomposición NMF, donde el ruido se modela de una forma genérica mediante restricciones matemáticas.[EN]This thesis is focused on the development of new classification and speech enhancement algorithms based, explicitly or implicitly, on the fundamental frequency (F0). The F0 of speech has a number of properties that enable speech discrimination from the remaining signals in the acoustic scene, either by defining F0-based signal features (for classification) or F0-based signal models (for separation). Three main contributions are included in this work: 1) an acoustic environment classification algorithm for hearing aids based on F0 to classify the input signal into speech and nonspeech classes; 2) a frame-by-frame basis voiced speech detection algorithm based on the aperiodicity measure, able to work under non-stationary noise and applicable to speech enhancement; 3) a speech denoising algorithm based on a regularized NMF decomposition, in which the background noise is described in a generic way with mathematical constraints.Tesis Univ. Jaén. Departamento de Ingeniería de Telecomunición. Leída el 11 de enero de 201

The role of perceptual integration in the recognition of assimilated word forms

We investigated how spoken words are recognized when they have been altered by phonological assimilation. Previous research has shown that there is a process of perceptual compensation for phonological assimilations. Three recently formulated proposals regarding the mechanisms for compensation for assimilation make different predictions with regard to the level at which compensation is supposed to occur as well as regarding the role of specific language experience. In the present study, Hungarian words and nonwords, in which a viable and an unviable liquid assimilation was applied, were presented to Hungarian and Dutch listeners in an identification task and a discrimination task. Results indicate that viably changed forms are difficult to distinguish from canonical forms independent of experience with the assimilation rule applied in the utterances. This reveals that auditory processing contributes to perceptual compensation for assimilation, while language experience has only a minor role to play when identification is required.peer-reviewe

Characterization of central auditory processing in minimally and low verbal adolescents with autism

Autism spectrum disorder (ASD) is a neurodevelopmental disorder in which individuals demonstrate deficits in social communication and repetitive or restricted behaviors or interests. About one-third never attain fluent expressive language and remain minimally or low verbal (ASD-MLV). We hypothesized that central auditory processing is particularly disrupted in ASD-MLV given the shared neural substrates of sound processing and language. To address this hypothesis, we conducted four empirical studies designed to capture neural and behavioral correlates of central auditory processing in children and adolescents who were either typically developing (TD), verbally fluent with ASD (ASD-V), or ASD-MLV. Our first study established that adult-like neural indices of sound organization as measured by mismatch responses (MMRs) during a passive stream segregation task were not observable until adolescence in TD participants, ages 3 to 21 (N=65). Findings led us to focus subsequent studies on adolescents. In our second study, we conducted a meta-analysis of experiments that had compared MMRs between TD and ASD samples (N=721). We identified that while there was some evidence suggesting that perceptual sound organization (as evidenced by MMR) was more dysfunctional in those with ASD, more research was needed to validate this pattern in adolescents and low verbal samples. In our third study (N=83), we determined that atypical auditory behaviors occurred most often in those with ASD with combined expressive and receptive language impairments; furthermore, the percentage of time exhibiting such behaviors was associated with weaker MMRs. In our final study (N=74), we quantified neural orienting responses to one’s own name in a multispeaker setting – a task that requires higher-order stream segregation and social auditory attention – in adolescents. We found that responses were weaker in ASD-MLV compared to ASD-V and TD participants. In addition, strength of response in those with ASD was negatively correlated with parent-reported signs of auditory-specific attentional deficits, as measured by the Short Sensory Profile Auditory Filtering Subscale. With this dissertation, we found atypical neural indices of auditory processing in ASD-MLV adolescents and discuss theoretical implications for why central auditory processing might be particularly pronounced in the ASD-MLV phenotype.2022-01-30T00:00:00

Infants' and Adults' Use of Temporal Cues in Consonant Discrimination

OBJECTIVES: Adults can use slow temporal envelope cues, or amplitude modulation (AM), to identify speech sounds in quiet. Faster AM cues and the temporal fine structure, or frequency modulation (FM), play a more important role in noise. This study assessed whether fast and slow temporal modulation cues play a similar role in infants' speech perception by comparing the ability of normal-hearing 3-month-olds and adults to use slow temporal envelope cues in discriminating consonants contrasts. DESIGN: English consonant-vowel syllables differing in voicing or place of articulation were processed by 2 tone-excited vocoders to replace the original FM cues with pure tones in 32 frequency bands. AM cues were extracted in each frequency band with 2 different cutoff frequencies, 256 or 8 Hz. Discrimination was assessed for infants and adults using an observer-based testing method, in quiet or in a speech-shaped noise. RESULTS: For infants, the effect of eliminating fast AM cues was the same in quiet and in noise: a high proportion of infants discriminated when both fast and slow AM cues were available, but less than half of the infants also discriminated when only slow AM cues were preserved. For adults, the effect of eliminating fast AM cues was greater in noise than in quiet: All adults discriminated in quiet whether or not fast AM cues were available, but in noise eliminating fast AM cues reduced the percentage of adults reaching criterion from 71 to 21%. CONCLUSIONS: In quiet, infants seem to depend on fast AM cues more than adults do. In noise, adults seem to depend on FM cues to a greater extent than infants do. However, infants and adults are similarly affected by a loss of fast AM cues in noise. Experience with the native language seems to change the relative importance of different acoustic cues for speech perception

Representation of speech in the primary auditory cortex and its implications for robust speech processing

Speech has evolved as a primary form of communication between humans. This most used means of communication has been the subject of intense study for years, but there is still a lot that we do not know about it. It is an oft repeated fact, that even the performance of the best speech processing algorithms still lags far behind that of the average human, It seems inescapable that unless we know more about the way the brain performs this task, our machines can not go much further. This thesis focuses on the question of speech representation in the brain, both from a physiological and technological perspective. We explore the representation of speech through the encoding of its smallest elements - phonemic features - in the primary auditory cortex. We report on how population of neurons with diverse tuning properties respond discriminately to phonemes resulting in explicit encoding of their parameters. Next, we show that this sparse encoding of the phonemic features is a simple consequence of the linear spectro-temporal properties of the auditory cortical neurons and that a Spectro-Temporal receptive field model can predict similar patterns of activation. This is an important step toward the realization of systems that operate based on the same principles as the cortex. Using an inverse method of reconstruction, we shall also explore the extent to which phonemic features are preserved in the cortical representation of noisy speech. The results suggest that the cortical responses are more robust to noise and that the important features of phonemes are preserved in the cortical representation even in noise. Finally, we explain how a model of this cortical representation can be used for speech processing and enhancement applications to improve their robustness and performance

Single-Microphone Speech Enhancement Inspired by Auditory System

Enhancing quality of speech in noisy environments has been an active area of research due to the abundance of applications dealing with human voice and dependence of their performance on this quality. While original approaches in the field were mostly addressing this problem in a pure statistical framework in which the goal was to estimate speech from its sum with other independent processes (noise), during last decade, the attention of the scientific community has turned to the functionality of human auditory system. A lot of effort has been put to bridge the gap between the performance of speech processing algorithms and that of average human by borrowing the models suggested for the sound processing in the auditory system. In this thesis, we will introduce algorithms for speech enhancement inspired by two of these models i.e. the cortical representation of sounds and the hypothesized role of temporal coherence in the auditory scene analysis. After an introduction to the auditory system and the speech enhancement framework we will first show how traditional speech enhancement technics such as wiener-filtering can benefit on the feature extraction level from discriminatory capabilities of spectro-temporal representation of sounds in the cortex i.e. the cortical model. We will next focus on the feature processing as opposed to the extraction stage in the speech enhancement systems by taking advantage of models hypothesized for human attention for sound segregation. We demonstrate a mask-based enhancement method in which the temporal coherence of features is used as a criterion to elicit information about their sources and more specifically to form the masks needed to suppress the noise. Lastly, we explore how the two blocks for feature extraction and manipulation can be merged into one in a manner consistent with our knowledge about auditory system. We will do this through the use of regularized non-negative matrix factorization to optimize the feature extraction and simultaneously account for temporal dynamics to separate noise from speech