Speaker Variability Research Articles

Identifying the Russian voiceless non-palatalized fricatives /f/, /s/, and /ʃ/ from acoustic cues using machine learning.

This paper shows that machine learning techniques are very successful at classifying the Russian voiceless non-palatalized fricatives [f], [s], and [ʃ] using a small set of acoustic cues. From a data sample of 6320 tokens of read sentences produced by 40 participants, temporal and spectral measurements are extracted from the full sound, the noise duration, and the middle 30 ms windows. Furthermore, 13 mel-frequency cepstral coefficients (MFCCs) are computed from the middle 30 ms window. Classifiers based on single decision trees, random forests, support vector machines, and neural networks are trained and tested to distinguish between these three fricatives. The results demonstrate that, first, the three acoustic cue extraction techniques are similar in terms of classification accuracy (93% and 99%) but that the spectral measurements extracted from the full frication noise duration result in slightly better accuracy. Second, the center of gravity and the spectral spread are sufficient for the classification of [f], [s], and [ʃ] irrespective of contextual and speaker variation. Third, MFCCs show a marginally higher predictive power over spectral cues (<2%). This suggests that both sets of measures provide sufficient information for the classification of these fricatives and their choice depends on the particular research question or application.

Acoustic and speaker variation in Dutch /n/ and /m/ as a function of phonetic context and syllabic position

In forensic speech science, nasals are often reported to be particularly useful in characterizing speakers because of their low within-speaker and high between-speaker variability. However, empirical acoustic data from nasal consonants indicate that there is a somewhat larger role for the oral cavity in nasal consonant acoustics than is generally predicted by acoustic models. For example, in read speech, nasal consonant acoustics show lingual coarticulation that differs by nasal consonant, and syllabic position also seems to affect realizations of nasal consonants within speakers. In the current exploratory study, the within- and between-speaker variation in the most frequent nasals in Standard Dutch, /n/ and /m/, was investigated. Using 3695 [n] and 3291 [m] tokens sampled from 54 speakers' spontaneous telephone utterances, linear mixed-effects modeling of acoustic-phonetic features showed effects of phonetic context that differed by nasal consonant and by syllabic position. A subsequent speaker-classification test using multinomial logistic regression on the acoustic-phonetic features seems to indicate that nasals displaying larger effects of phonetic context also perform slightly better in speaker classification, although differences were minor. This might be caused by between-speaker variation in the degree and timing of lingual coarticulatory gestures.

Sociophonetic variation in English /l/ in the child-directed speech of English-Malay bilinguals

Three realisations of syllable-final /l/ have been described in previous work on Singapore English: vocalised-l (or deleted-l in some phonetic contexts; the local norms), dark-l (a form associated with the exonormative standards), and clear-l (a Malay-derived phonetic trait observed in the speech of some English-Malay bilinguals). This study examined whether, how and why Singaporean English-Malay bilinguals vary their English /l/ in their child-directed speech, and whether the phonetic variation, if any, could be socially-conditioned. The laterals in the English child-directed speech of ten father-mother dyads with their preschoolers were analysed using auditory and acoustic methods. All participants were simultaneous or early English-Malay bilinguals. The findings revealed that in informal contexts, both mothers and fathers used a relatively clearer /l/ in all syllable positions. Contrastingly, in formal contexts that involved teaching and learning, the coda laterals of mothers were significantly darker, thereby exhibiting positional contrast between onset and coda laterals. They also produced significantly more vocalised-l in these contexts. Fathers, however, did not show differentiation in the darkness of the laterals, nor did their laterals show significant positional differences in formal contexts, although some fathers of younger children did produce more vocalised-l than they did in informal contexts. The variation observed was discussed by exploring the potential socio-indexical meanings of these variants of /l/ within the context of variationist accounts of Singapore English and by drawing parallels with socially-conditioned variation in bilectal monolinguals and ethnolect speakers. Differences between maternal and paternal CDS patterns could be attributed to gender roles and cultural expectations of mothers’ dominant role in child-rearing, and may also be a result of and enabled by Malay women’s potentially more complex repertoire range.

Perception of native and non-native phonemic contrasts in children with autistic spectrum disorder: effects of speaker variability

ABSTRACT The current study investigated speech perception in children with ASD by directly comparing discrimination accuracy of phonemic contrasts in the native and non-native languages. The effect of speaker variability on phoneme perception was also examined. We also explored the relation between language impairment and accuracy in phoneme discrimination in children with ASD. Significant differences in performance were found between the ASD and TD groups on discrimination of the native phonemic contrasts. By contrast, no difference was found between the two groups on discrimination of the non-native phonemic contrasts. Further subgroup analysis revealed that the ALN group (ASD without language delay or impairment) showed significantly higher discrimination accuracy for the native syllable contrasts than the non-native counterpart. No significant difference was found in the discrimination accuracy between the native and non-native phonemic contrasts in the ALD group (ASD with language delay or impairment). The effect of speaker viability on phoneme discrimination was observed in the TD group but not in the ASD subgroups. Nonverbal reasoning ability was highly related to discrimination accuracy of both the native and non-native phonemic contrasts in children with ASD. The results of the present study suggest that speech perception in children with ASD is not as attuned to their native language as in their TD peers. Our findings also indicate that language delay or impairment is related to difficulty in perception of native phonemes in children with ASD.

Examining the Relationship Between Speech Perception, Production Distinctness, and Production Variability.

Several studies have demonstrated that individuals’ ability to perceive a speech sound contrast is related to the production of that contrast in their native language. The theoretical account for this relationship is that speech perception and production have a shared multimodal representation in relevant sensory spaces (e.g., auditory and somatosensory domains). This gives rise to a prediction that individuals with more narrowly defined targets will produce greater separation between contrasting sounds, as well as lower variability in the production of each sound. However, empirical studies that tested this hypothesis, particularly with regard to variability, have reported mixed outcomes. The current study investigates the relationship between perceptual ability and production ability, focusing on the auditory domain. We examined whether individuals’ categorical labeling consistency for the American English /ε/–/æ/ contrast, measured using a perceptual identification task, is related to distance between the centroids of vowel categories in acoustic space (i.e., vowel contrast distance) and to two measures of production variability: the overall distribution of repeated tokens for the vowels (i.e., area of the ellipse) and the proportional within-trial decrease in variability as defined as the magnitude of self-correction to the initial acoustic variation of each token (i.e., centering ratio). No significant associations were found between categorical labeling consistency and vowel contrast distance, between categorical labeling consistency and area of the ellipse, or between categorical labeling consistency and centering ratio. These null results suggest that the perception-production relation may not be as robust as suggested by a widely adopted theoretical framing in terms of the size of auditory target regions. However, the present results may also be attributable to choices in implementation (e.g., the use of model talkers instead of continua derived from the participants’ own productions) that should be subject to further investigation.

Joint speaker separation and recognition using non-negative matrix deconvolution with adaptive dictionary

In this article, we propose a new method for joint cochannel speaker separation and recognition called adaptive-dictionary non-negative matrix deconvolution (DANMD). This method is an extension of non-negative matrix deconvolution (NMD) which models spectrogram matrix as a linear combination of dictionary elements (atoms). We propose a dictionary which is a linear combination of speaker-independent component and components representing speaker variability. The dictionary is parametric and all atoms depend on a small number of parameters. The speaker-independent component and components representing speaker variability are learned from recordings of tens or hundreds of speakers. We show that the proposed method can be applied to the single-channel speech separation task where two speakers of unknown identity are to be separated. In a scenario where the unknown speakers’ recordings are in training dataset together with recordings of many other speakers, we show that the proposed method outperforms stacked NMD (NMD with a dictionary which contains atoms of all speakers in the dataset) in terms of signal-to-distortion ratio (SDR). DANMD was also tested in a scenario where recordings of the recognized speakers were not in the training dataset. In this case it brought clearly positive signal-to-distortion ratios. The proposed model was also tested for a co-channel speaker identification task, where the parameters of the adapted model are a basis for a decision about the identity of the speakers in the mixture. In this case, the accuracy was 81.2 in comparison to 84.1 in the case of stacked NMD. While the speaker recognition accuracy is lower for the new approach, we find the primary value in the improved SDR.

Phrase-final intonation adjustment in Lebanese Arabic

Intonation languages such as English and German have been described as having, among others, ‘realizational’ differences with regard to their intonation (Ladd 1996). One such difference is whether phrase-final pitch contours that lack sufficient segmental material to be realized naturally are subjected to truncation or compression. The current investigation examines this question in Lebanese Arabic. Stimuli were created with decreasing segmental material (disyllabic phrase-final, monosyllabic phrase-final) for both statements and questions. The contours produced by 16 speakers consisted of rises (questions) and rise-falls (statements). Results indicate that reducing the segmental material induces compression in rises and truncation in rise-falls, supporting the claim that languages cannot simply be divided into compressing versus truncating languages, and that the shape of the intonational contour plays a role in accommodation strategies. Speaker variation is also discussed.

Contour clustering: A field-data-driven approach for documenting and analysing prototypical f0 contours

ABSTRACTThis paper reports an automatic data-driven analysis for describing prototypical intonation patterns, particularly suitable for initial stages of prosodic research and language description. The approach has several advantages over traditional ways to investigate intonation, such as the applicability to spontaneous speech, language- and domain-independency, and the potential of revealing meaningful functions of intonation. These features make the approach particularly useful for language documentation, where the description of prosody is often lacking. The core of this approach is a cluster analysis on a time-series of f0 measurements and consists of two scripts (Praat and R, available from https://constantijnkaland.github.io/contourclustering/). Graphical user interfaces can be used to perform the analyses on collected data ranging from spontaneous to highly controlled speech. There is limited need for manual annotation prior to analysis and speaker variability can be accounted for. After cluster analysis, Praat textgrids can be generated with the cluster number annotated for each individual contour. Although further confirmatory analysis is still required, the outcomes provide useful and unbiased directions for any investigation of prototypical f0 contours based on their acoustic form.

Compensation Techniques for Speaker Variability in Continuous Emotion Prediction

Continuous time-varying prediction of emotions based on speech in terms of attributes (i.e., arousal) has received considerable attention in the past few years. However, the variability introduced by factors not related to emotion, such as speaker and phonetic variability, which in turn may lead to less reliable models and less accurate emotion predictions, has not been fully explored yet. In particular, even though speaker variability has been shown to be a significant confounding factor in continuous emotion prediction systems, there remains a paucity of analyses about how speaker variability affects continuous emotion prediction systems and which methods can be applied to compensate for this variability. This paper first formulates speaker variability systematically in terms of probability distributions in both feature and model spaces, and quantifies the effect of speaker variability by comparing inter- and intra-speaker variability between speaker-dependent models. Second, two compensation techniques based on partial least squares dimensional reduction and feature mapping are proposed. Finally, the effectiveness of the proposed techniques is validated on three databases, across which they show consistent improvement in arousal, valence and dominance prediction. Additional quantitative analyse reveals that the two proposed techniques compensate for speaker variability in both the feature and model spaces simultaneously.

Is 10 Better than 1? The Effect of Speaker Variability on Children’s Cross-Situational Word Learning

ABSTRACT The current study examined the effect of speaker variability on children’s cross-situational word learning (XSWL). The study also examined the role of bilingual experience and sustained attention. Forty English monolingual children and 40 Spanish-English bilingual children ages 4–7 completed a XSWL task in a Single Speaker Condition and a Multiple Speaker Condition. Results indicated that speaker variability neither facilitated nor hindered XSWL. While monolingual children outperformed bilingual children, speaker-variability effects did not fluctuate across the two language groups. Notably, exposure to multiple speakers facilitated XSWL in children with poorer sustained attention skills, suggesting that variability in the input may be especially useful to children with poorer cognitive processing abilities.

Reconsidering variability in child speech production

Child speech is highly variable between and within speakers. This pattern has traditionally been explained by a lack of motor routine and articulatory control in the developing speech-motor apparatus. But the assumption that child speech is inherently variable—and the result of motor development and control—may be premature. Recent work suggests that some child speech variation may instead be attributable to errors in measurement: children's high fundamental frequencies make many traditional acoustic measures, such as formant tracking, unreliable and variable. Additionally, child speech variation can often be explained by experiential factors, such as the size of the lexicon or the type and quantity of language exposure. This talk will report on these and other recent findings that suggest a need to reconsider the prevalence of, and reasons for, variability in young children's speech.

Prosodic event detection in children’s read speech

Prosody is the supra-segmental aspect of speech that helps to convey the structure and intended meaning of lexical content unambiguously. The automatic detection of prosodic events, such as phrase boundary and word prominence, has a number of applications in discourse analysis, where a combination of syntactic and acoustic-prosodic features is typically employed. This work addresses prosodic event detection in the context of assessing oral reading skills of middle-school children. We discuss the observed characteristics of a specially created labeled data set of oral reading recordings of English stories by non-native speakers. The obtained diversity of language skills adds to the known challenges of high speaker variability in the acoustic realization of prosodic events. A combination of knowledge- and data-driven feature selection is implemented to identify a compact set of word-level features from the acoustic correlates of prosody considering different ways of incorporating the necessary temporal context. The system is benchmarked with reference to a widely known prosodic event recognition system in a speaker-independent set-up to obtain a competitive performance with greatly reduced feature dimensionality. The interpretable features enable us to use the predictor model importance scores to identify high-level speaker traits that influence the acoustic realization of prosodic events, suggesting a potential extension to systems that can extract and utilize speaker idiosyncrasies for superior prosodic event detection.

Training augmentation with TANDEM acoustic modelling in Punjabi adult speech recognition system

Processing of low resource pre and post acoustic signals always faced the challenge of data scarcity in its training module. It’s difficult to obtain high system accuracy with limited corpora in train set which results into extraction of large discriminative feature vector. These vectors information are distorted due to acoustic mismatch occurs because of real environment and inter speaker variations. In this paper, context independent information of an input speech signal is pre-processed using bottleneck features and later in modeling phase Tandem-NN model has been employ to enhance system accuracy. Later to fulfill the requirement of train data issues, in-domain training augmentation is perform using fusion of original clean and artificially created modified train noisy data and to further boost this training data, tempo modification of input speech signal is perform with maintenance of its spectral envelope and pitch in corresponding input audio signal. Experimental result shows that a relative improvement of 13.53% is achieved in clean and 32.43% in noisy conditions with Tandem-NN system in comparison to that of baseline system respectively.

A New Proposal for Phoneme Acquisition: Computing Speaker-Specific Distribution.

Speech is an acoustically variable signal, and one of the sources of this variation is the presence of multiple speakers. Empirical evidence has suggested that adult listeners possess remarkably sensitive (and systematic) abilities to process speech signals, despite speaker variability. It includes not only a sensitivity to speaker-specific variation, but also an ability to utilize speaker variation with other sources of information for further processing. Recently, many studies also showed that young children seem to possess a similar capacity. This suggests continuity in the processing of speaker-dependent speech variability, and suggests that this ability could also be important for infants learning their native language. In the present paper, we review evidence for speaker variability and speech processing in adults, and speaker variability and speech processing in young children, with an emphasis on how they make use of speaker-specific information in word learning situations. Finally, we will build on these findings to make a novel proposal for the use of speaker-specific information processing in phoneme learning in infancy.

Phonological Variation in Hijazi and Cairene Arabic: The Case of the Uvular Stop /q/

This small scale, qualitatively based, exploratory study aimed at exploring and analysing voice pattern production of eight participants (2 male and 6 female) by eliciting their voice patterns generated from reading forty-three words from a word list and also, from reading a short paragraph. Furthermore, the study aimed at exploring the phonological variation in the spoken Arabic of two regions: Jeddah, Saudi Arabia (Hijazi Arabic—HA) and Cairo, Egypt (Cairene Arabic—CA) and also, examines the role of age, sex, educational level and region on this variation. In particular, the study explored the correlation of voice patterns production as they relate to the non-linguistic factors such as age, gender and educational level. The analysis of the gathered qualitative data was carried out by transcribing the recorded data and coding each voice pattern in question. The results indicated that there is more variation in CA speakers than in HA speakers and also, there are some gender influences on phonological production.

An Acoustic Analysis of Fluctuations for Inter and Intra Speaker Variability in Speech Sounds

An Acoustic Analysis of Fluctuations for Inter and Intra Speaker Variability in Speech Sounds

An Acoustic Analysis of Fluctuations for Inter and Intra Speaker Variability in Speech Sounds

An Acoustic Analysis of Fluctuations for Inter and Intra Speaker Variability in Speech Sounds

Segmental diagnostics of neurogenic and functional foreign accent syndrome

Abstract Previous research suggests differences in speech patterns between speakers with foreign accent syndrome (FAS) associated with a neurological (neurogenic FAS) versus a psychological aetiology (functional FAS). Differentiating sub-types holds important clinical implications, affecting the nature of follow-up assessment and treatment. To date, there exist no systematic comparisons between these sub-groups. To investigate possible differences, we employed auditory and acoustic analyses to compare schwa insertion and /r/production in speakers with FAS (12 neurogenic, 5 functional). Schwa insertion and /r/ production demonstrated significant differences between groups. Neurogenic aetiology was associated with higher within and between speaker performance consistency and congruence of derailments with phonetic-phonological and neurological accounts of ‘error’ origin. Individuals with functional FAS showed significant within and between speaker variability, which was poorly accounted for by linguistic and speech motor control explanations. We argue that schwa insertion and differences in /r/ realisations provide reliable and accessible variables for clinicians to employ to support differential diagnosis of functional versus neurogenic speech disorders. Findings are discussed in the context of understanding FAS and the broader context of understanding functional speech and language disorders.

Individual variability in auditory feedback processing: Responses to real-time formant perturbations and their relation to perceptual acuity

In this study, both between-subject and within-subject variability in speech perception and speech production were examined in the same set of speakers. Perceptual acuity was determined using an ABX auditory discrimination task, whereby speakers made judgments between pairs of syllables on a /ɛ/ to /æ/ acoustic continuum. Auditory feedback perturbations of the first two formants were implemented in a production task to obtain measures of compensation, normal speech production variability, and vowel spacing. Speakers repeated the word "head" 120 times under varying feedback conditions, with the final Hold phase involving the strongest perturbations of +240 Hz in F1 and -300 Hz in F2. Multiple regression analyses were conducted to determine whether individual differences in compensatory behavior in the Hold phase could be predicted by perceptual acuity, speech production variability, and vowel spacing. Perceptual acuity significantly predicted formant changes in F1, but not in F2. These results are discussed in consideration of the importance of using larger sample sizes in the field and developing new methods to explore feedback processing at the individual participant level. The potential positive role of variability in speech motor control is also considered.

Speaker Variations in Pitch Alignment of English Loanwords

Speaker Variations in Pitch Alignment of English Loanwords