Estimating Speaking Rate by Means of Rhythmicity Parameters

In this paper we present a speech rate estimator based on so-called rhythmicity features derived from a modified version of the short-time energy envelope. To evaluate the new method, it is compared to a traditional speech rate estimator on the basis of semi-automatic segmentation. Speech material from the Alcohol Language Corpus (ALC) covering intoxicated and sober speech of different speech styles provides a statistically sound foundation to test upon. The proposed measure clearly correlates with the semi-automatically determined speech rate and seems to be robust across speech styles and speaker states

Involvement of the cortico-basal ganglia-thalamocortical loop in developmental stuttering

Stuttering is a complex neurodevelopmental disorder that has to date eluded a clear explication of its pathophysiological bases. In this review, we utilize the Directions Into Velocities of Articulators (DIVA) neurocomputational modeling framework to mechanistically interpret relevant findings from the behavioral and neurological literatures on stuttering. Within this theoretical framework, we propose that the primary impairment underlying stuttering behavior is malfunction in the cortico-basal ganglia-thalamocortical (hereafter, cortico-BG) loop that is responsible for initiating speech motor programs. This theoretical perspective predicts three possible loci of impaired neural processing within the cortico-BG loop that could lead to stuttering behaviors: impairment within the basal ganglia proper; impairment of axonal projections between cerebral cortex, basal ganglia, and thalamus; and impairment in cortical processing. These theoretical perspectives are presented in detail, followed by a review of empirical data that make reference to these three possibilities. We also highlight any differences that are present in the literature based on examining adults versus children, which give important insights into potential core deficits associated with stuttering versus compensatory changes that occur in the brain as a result of having stuttered for many years in the case of adults who stutter. We conclude with outstanding questions in the field and promising areas for future studies that have the potential to further advance mechanistic understanding of neural deficits underlying persistent developmental stuttering.R01 DC007683 - NIDCD NIH HHS; R01 DC011277 - NIDCD NIH HHSPublished versio

Correlates of linguistic rhythm in the speech signal

Spoken languages have been classified by linguists according to their rhythmic properties, and psycholinguists have relied on this classification to account for infants’ capacity to discriminate languages. Although researchers have measured many speech signal properties, they have failed to identify reliable acoustic characteristics for language classes. This paper presents instrumental measurements based on a consonant/vowel segmentation for eight languages. The measurements suggest that intuitive rhythm types reflect specific phonological properties, which in turn are signaled by the acoustic/phonetic properties of speech. The data support the notion of rhythm classes and also allow the simulation of infant language discrimination, consistent with the hypothesis that newborns rely on a coarse segmentation of speech. A hypothesis is proposed regarding the role of rhythm perception in language acquisition

Unsupervised spoken keyword spotting and learning of acoustically meaningful units

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009.Cataloged from PDF version of thesis.Includes bibliographical references (p. 103-106).The problem of keyword spotting in audio data has been explored for many years. Typically researchers use supervised methods to train statistical models to detect keyword instances. However, such supervised methods require large quantities of annotated data that is unlikely to be available for the majority of languages in the world. This thesis addresses this lack-of-annotation problem and presents two completely unsupervised spoken keyword spotting systems that do not require any transcribed data. In the first system, a Gaussian Mixture Model is trained to label speech frames with a Gaussian posteriorgram, without any transcription information. Given several spoken samples of a keyword, a segmental dynamic time warping is used to compare the Gaussian posteriorgrams between keyword samples and test utterances. The keyword detection result is then obtained by ranking the distortion scores of all the test utterances. In the second system, to avoid the need for spoken samples, a Joint-Multigram model is used to build a mapping from the keyword text samples to the Gaussian component indices. A keyword instance in the test data can be detected by calculating the similarity score of the Gaussian component index sequences between keyword samples and test utterances. The proposed two systems are evaluated on the TIMIT and MIT Lecture corpus. The result demonstrates the viability and effectiveness of the two systems. Furthermore, encouraged by the success of using unsupervised methods to perform keyword spotting, we present some preliminary investigation on the unsupervised detection of acoustically meaningful units in speech.by Yaodong Zhang.S.M

Educational neuroscience: Neural structure-mapping and the promise of oscillations

A critical goal for educational neuroscience is to specify causal developmental mechanisms of learning. In-depth understanding of neural information coding and transmission should enable understanding of how sensory systems build the cognitive systems critical for education–language, attention, memory-over developmental time. Cortical oscillatory encoding processes may offer mechanistic insights into how developmental trajectories unfold. All educators are familiar with children who show mastery of taught information one week, yet subsequently appear to lose it. Oscillatory research shows that sensory information that arrives out of phase with ongoing oscillations does not reach awareness, while complex combinations of bottom-up and top-down phase-phase and phase-power relations enable context and prior knowledge to influence current performance. Oscillatory studies of language are used to illustrate the promise of oscillations research for education.MRC (G0902375)This is the author accepted manuscript. The final version is available from Elsevier via http://dx.doi.org/10.1016/j.cobeha.2016.05.011

Entraining the Brain: Applications to Language Research and Links to Musical Entrainment

Clayton’s paper provides a clear and accessible summary of the significance of entrainment for music making, and for human behaviour in general. He notes the central role of metrical structure in musical entrainment, the possible role of oscillatory neural activity, and the core notion of phase alignment. Here I show how these same factors are central to speech processing by the human brain. I argue that entrainment to metrical structure is core to linguistic as well as musical human behaviour. I illustrate this view using entrainment data from developmental dyslexia. The core role of entrainment in efficient speech processing suggests that language difficulties in childhood may benefit from music-based remediation that focuses on multi-modal rhythmic entrainment. Alignment of linguistic and musical metrical structure seems likely to be fundamental to successful remediation

A computer based analysis of the effects of rhythm modification on the intelligibility of the speech of hearing and deaf subjects

The speech of profoundly deaf persons often exhibits acquired unnatural rhythms, or a random pattern of rhythms. Inappropriate pause-time and speech-time durations are common in their speech. Specific rhythm deficiencies include abnormal rate of syllable utterance, improper grouping, poor timing and phrasing of syllables and unnatural stress for accent and emphasis. Assuming that temporal features are fundamental to the naturalness of spoken language, these abnormal timing patterns are often detractive. They may even be important factors in the decreased intelligibility of the speech. This thesis explores the significance of temporal cues in the rhythmic patterns of speech. An analysis-synthesis approach was employed based on the encoding and decoding of speech by a tandem chain of digital computer operations. Rhythm as a factor in the speech intelligibility of deaf and normal-hearing subjects was investigated. The results of this study support the general hypothesis that rhythm and rhythmic intuition are important to the perception of speech