Impact of pallidotomy on physiological articulation function and speech intelligibility in Parkinsons disease

The objective of this study was to evaluate the effects of posteroventral pallidotomy on perceptual and physiological measures of articulatory function and speech intelligibility in Parkinson disease (M). The study examined 11 participants with M who underwent posteroventral pallidotomy Physiological measures of hp and tongue function. and perceptual measures of speech intelligibility were obtained prepallidotomy and 3 months postpallidotomy. The participants with PD were also assessed on the Unified Parkinsons Disease Rating Scale (UPDRS Part III) In addition, the study included a group of 16 participants with PD who did not undergo pallidotomy and a group of 30 nonneurologically impaired participants. Analyses of physiological articulatory function and speech intelligibility did not reveal corresponding improvements in motor speech function as observed in general limb motor function postpallidotomy. Overall, individual reliable change analyses revealed that the majority of surgical PD participants demonstrated no reliable change on perceptual and physiological measures of articulation. The cur rent study revealed preliminary evidence that articulatury function and speech intelligibility did not change following posteroventral pallidotomy in a group of individuals with PD.

Speech production in Parkinson's disease: II. Acoustic and electropalatographic investigation of sentence, word and segment durations

Previous investigations employing electropalatography (EPG) have identified articulatory timing deficits in individuals with acquired dysarthria. However, this technology is yet to be applied to the articulatory timing disturbance present in Parkinson's disease (PD). As a result, the current investigation aimed to use EPG to comprehensively examine the temporal aspects of articulation in a group of nine individuals with PD at sentence, word and segment level. This investigation followed on from a prior study (McAuliffe, Ward and Murdoch) and similarly, aimed to compare the results of the participants with PD to a group of aged (n=7) and young controls (n=8) to determine if ageing contributed to any articulatory timing deficits observed. Participants were required to read aloud the phrase I saw a ___ today'' with the EPG palate in-situ. Target words included the consonants /1/, /s/ and /t/ in initial position in both the /i/ and /a/ vowel environments. Perceptual investigation of speech rate was conducted in addition to objective measurement of sentence, word and segment duration. Segment durations included the total segment length and duration of the approach, closure/constriction and release phases of EPG consonant production. Results of the present study revealed impaired speech rate, perceptually, in the group with PD. However, this was not confirmed objectively. Electropalatographic investigation of segment durations indicated that, in general, the group with PD demonstrated segment durations consistent with the control groups. Only one significant difference was noted, with the group with PD exhibiting significantly increased duration of the release phase for /1a/ when compared to both the control groups. It is, therefore, possible that EPG failed to detect lingual movement impairment as it does not measure the complete tongue movement towards and away from the hard palate. Furthermore, the contribution of individual variation to the present findings should not be overlooked.

The perceptual organization of sine-wave speech under competitive conditions

Speech comprises dynamic and heterogeneous acoustic elements, yet it is heard as a single perceptual stream even when accompanied by other sounds. The relative contributions of grouping “primitives” and of speech-specific grouping factors to the perceptual coherence of speech are unclear, and the acoustical correlates of the latter remain unspecified. The parametric manipulations possible with simplified speech signals, such as sine-wave analogues, make them attractive stimuli to explore these issues. Given that the factors governing perceptual organization are generally revealed only where competition operates, the second-formant competitor (F2C) paradigm was used, in which the listener must resist competition to optimize recognition [Remez et al., Psychol. Rev. 101, 129-156 (1994)]. Three-formant (F1+F2+F3) sine-wave analogues were derived from natural sentences and presented dichotically (one ear = F1+F2C+F3; opposite ear = F2). Different versions of F2C were derived from F2 using separate manipulations of its amplitude and frequency contours. F2Cs with time-varying frequency contours were highly effective competitors, regardless of their amplitude characteristics. In contrast, F2Cs with constant frequency contours were completely ineffective. Competitor efficacy was not due to energetic masking of F3 by F2C. These findings indicate that modulation of the frequency, but not the amplitude, contour is critical for across-formant grouping.

The human factors of automatic speech recognition in control room systems

This thesis addresses the viability of automatic speech recognition for control room systems; with careful system design, automatic speech recognition (ASR) devices can be useful means for human computer interaction in specific types of task. These tasks can be defined as complex verbal activities, such as command and control, and can be paired with spatial tasks, such as monitoring, without detriment. It is suggested that ASR use be confined to routine plant operation, as opposed the critical incidents, due to possible problems of stress on the operators' speech.  It is proposed that using ASR will require operators to adapt a commonly used skill to cater for a novel use of speech. Before using the ASR device, new operators will require some form of training. It is shown that a demonstration by an experienced user of the device can lead to superior performance than instructions. Thus, a relatively cheap and very efficient form of operator training can be supplied by demonstration by experienced ASR operators. From a series of studies into speech based interaction with computers, it is concluded that the interaction be designed to capitalise upon the tendency of operators to use short, succinct, task specific styles of speech. From studies comparing different types of feedback, it is concluded that operators be given screen based feedback, rather than auditory feedback, for control room operation. Feedback will take two forms: the use of the ASR device will require recognition feedback, which will be best supplied using text; the performance of a process control task will require task feedback integrated into the mimic display. This latter feedback can be either textual or symbolic, but it is suggested that symbolic feedback will be more beneficial. Related to both interaction style and feedback is the issue of handling recognition errors. These should be corrected by simple command repetition practices, rather than use error handling dialogues. This method of error correction is held to be non intrusive to primary command and control operations. This thesis also addresses some of the problems of user error in ASR use, and provides a number of recommendations for its reduction.

Assessment of time frequency warping for use as a reference degradation for assessing synthetic speech

At present there is no standard assessment method for rating and comparing the quality of synthesized speech. This study assesses the suitability of Time Frequency Warping (TFW) modulation for use as a reference device for assessing synthesized speech. Time Frequency Warping modulation introduces timing errors into natural speech that produce perceptual errors similar to those found in synthetic speech. It is proposed that TFW modulation used in conjunction with a listening effort test would provide a standard assessment method for rating the quality of synthesized speech. This study identifies the most suitable TFW modulation variable parameter to be used for assessing synthetic speech and assess the results of several assessment tests that rate examples of synthesized speech in terms of the TFW variable parameter and listening effort. The study also attempts to identify the attributes of speech that differentiate synthetic, TFW modulated and natural speech.

A comparison of microphone and speech recognition engine efficacy for mobile data entry

The research presented in this paper is part of an ongoing investigation into how best to incorporate speech-based input within mobile data collection applications. In our previous work [1], we evaluated the ability of a single speech recognition engine to support accurate, mobile, speech-based data input. Here, we build on our previous research to compare the achievable speaker-independent accuracy rates of a variety of speech recognition engines; we also consider the relative effectiveness of different speech recognition engine and microphone pairings in terms of their ability to support accurate text entry under realistic mobile conditions of use. Our intent is to provide some initial empirical data derived from mobile, user-based evaluations to support technological decisions faced by developers of mobile applications that would benefit from, or require, speech-based data entry facilities.

Novel speech signal processing algorithms for high-accuracy classification of Parkinson's disease

There has been considerable recent research into the connection between Parkinson's disease (PD) and speech impairment. Recently, a wide range of speech signal processing algorithms (dysphonia measures) aiming to predict PD symptom severity using speech signals have been introduced. In this paper, we test how accurately these novel algorithms can be used to discriminate PD subjects from healthy controls. In total, we compute 132 dysphonia measures from sustained vowels. Then, we select four parsimonious subsets of these dysphonia measures using four feature selection algorithms, and map these feature subsets to a binary classification response using two statistical classifiers: random forests and support vector machines. We use an existing database consisting of 263 samples from 43 subjects, and demonstrate that these new dysphonia measures can outperform state-of-the-art results, reaching almost 99% overall classification accuracy using only ten dysphonia features. We find that some of the recently proposed dysphonia measures complement existing algorithms in maximizing the ability of the classifiers to discriminate healthy controls from PD subjects. We see these results as an important step toward noninvasive diagnostic decision support in PD.

A comparison of microphone and speech recognition engine efficacy for mobile data entry

The research presented in this paper is part of an ongoing investigation into how best to incorporate speech-based input within mobile data collection applications. In our previous work [1], we evaluated the ability of a single speech recognition engine to support accurate, mobile, speech-based data input. Here, we build on our previous research to compare the achievable speaker-independent accuracy rates of a variety of speech recognition engines; we also consider the relative effectiveness of different speech recognition engine and microphone pairings in terms of their ability to support accurate text entry under realistic mobile conditions of use. Our intent is to provide some initial empirical data derived from mobile, user-based evaluations to support technological decisions faced by developers of mobile applications that would benefit from, or require, speech-based data entry facilities.

Speech and non-speech stimuli in the prediction of early reading skills:the influence of processing demands and response-type

Purpose: Both phonological (speech) and auditory (non-speech) stimuli have been shown to predict early reading skills. However, previous studies have failed to control for the level of processing required by tasks administered across the two levels of stimuli. For example, phonological tasks typically tap explicit awareness e.g., phoneme deletion, while auditory tasks usually measure implicit awareness e.g., frequency discrimination. Therefore, the stronger predictive power of speech tasks may be due to their higher processing demands, rather than the nature of the stimuli. Method: The present study uses novel tasks that control for level of processing (isolation, repetition and deletion) across speech (phonemes and nonwords) and non-speech (tones) stimuli. 800 beginning readers at the onset of literacy tuition (mean age 4 years and 7 months) were assessed on the above tasks as well as word reading and letter-knowledge in the first part of a three time-point longitudinal study. Results: Time 1 results reveal a significantly higher association between letter-sound knowledge and all of the speech compared to non-speech tasks. Performance was better for phoneme than tone stimuli, and worse for deletion than isolation and repetition across all stimuli. Conclusions: Results are consistent with phonological accounts of reading and suggest that level of processing required by the task is less important than stimuli type in predicting the earliest stage of reading.

Investigating microphone efficacy for facilitation of mobile speech-based data entry

Despite being nominated as a key potential interaction technique for supporting today's mobile technology user, the widespread commercialisation of speech-based input is currently being impeded by unacceptable recognition error rates. Developing effective speech-based solutions for use in mobile contexts, given the varying extent of background noise, is challenging. The research presented in this paper is part of an ongoing investigation into how best to incorporate speechbased input within mobile data collection applications. Specifically, this paper reports on a comparison of three different commercially available microphones in terms of their efficacy to facilitate mobile, speech-based data entry. We describe, in detail, our novel evaluation design as well as the results we obtained.

A Cognitive Science Reasoning in Recognition of Emotions in Audio-Visual Speech

In this report we summarize the state-of-the-art of speech emotion recognition from the signal processing point of view. On the bases of multi-corporal experiments with machine-learning classifiers, the observation is made that existing approaches for supervised machine learning lead to database dependent classifiers which can not be applied for multi-language speech emotion recognition without additional training because they discriminate the emotion classes following the used training language. As there are experimental results showing that Humans can perform language independent categorisation, we made a parallel between machine recognition and the cognitive process and tried to discover the sources of these divergent results. The analysis suggests that the main difference is that the speech perception allows extraction of language independent features although language dependent features are incorporated in all levels of the speech signal and play as a strong discriminative function in human perception. Based on several results in related domains, we have suggested that in addition, the cognitive process of emotion-recognition is based on categorisation, assisted by some hierarchical structure of the emotional categories, existing in the cognitive space of all humans. We propose a strategy for developing language independent machine emotion recognition, related to the identification of language independent speech features and the use of additional information from visual (expression) features.

The roles of family history of dyslexia, language, speech production and phonological processing in predicting literacy progress

It is well established that speech, language and phonological skills are closely associated with literacy, and that children with a family risk of dyslexia (FRD) tend to show deficits in each of these areas in the preschool years. This paper examines what the relationships are between FRD and these skills, and whether deficits in speech, language and phonological processing fully account for the increased risk of dyslexia in children with FRD. One hundred and fifty-three 4-6-year-old children, 44 of whom had FRD, completed a battery of speech, language, phonology and literacy tasks. Word reading and spelling were retested 6 months later, and text reading accuracy and reading comprehension were tested 3 years later. The children with FRD were at increased risk of developing difficulties in reading accuracy, but not reading comprehension. Four groups were compared: good and poor readers with and without FRD. In most cases good readers outperformed poor readers regardless of family history, but there was an effect of family history on naming and nonword repetition regardless of literacy outcome, suggesting a role for speech production skills as an endophenotype of dyslexia. Phonological processing predicted spelling, while language predicted text reading accuracy and comprehension. FRD was a significant additional predictor of reading and spelling after controlling for speech production, language and phonological processing, suggesting that children with FRD show additional difficulties in literacy that cannot be fully explained in terms of their language and phonological skills. It is well established that speech, language and phonological skills are closely associated with literacy, and that children with a family risk of dyslexia (FRD) tend to show deficits in each of these areas in the preschool years. This paper examines what the relationships are between FRD and these skills, and whether deficits in speech, language and phonological processing fully account for the increased risk of dyslexia in children with FRD. One hundred and fifty-three 4-6-year-old children, 44 of whom had FRD, completed a battery of speech, language, phonology and literacy tasks. © 2014 John Wiley & Sons Ltd.

Literacy, numeracy and learning in school-aged children identified as having speech and language impairment in early childhood

The progress of a nationally representative sample of 3632 children was followed from early childhood through to primary school, using data from the Longitudinal Study of Australian Children (LSAC). The aim was to examine the predictive effects of different aspects of communicative ability, and of early vs. sustained identification of speech and language impairment, on children's achievement and adjustment at school. Four indicators identified speech and language impairment: parent-rated expressive language concern; parent-rated receptive language concern; use of speech-language pathology services; below average scores on the adapted Peabody Picture Vocabulary Test-III. School outcomes were assessed by teachers' ratings of language/literacy ability, numeracy/mathematical thinking and approaches to learning. Comparison of group differences, using ANOVA, provided clear evidence that children who were identified as having speech and language impairment in their early childhood years did not perform as well at school, two years later, as their non-impaired peers on all three outcomes: Language and Literacy, Mathematical Thinking, and Approaches to Learning. The effects of early speech and language status on literacy, numeracy, and approaches to learning outcomes were similar in magnitude to the effect of family socio-economic factors, after controlling for child characteristics. Additionally, early identification of speech and language impairment (at age 4-5) was found to be a better predictor of school outcomes than sustained identification (at aged 4-5 and 6-7 years). Parent-reports of speech and language impairment in early childhood are useful in foreshadowing later difficulties with school and providing early intervention and targeted support from speech-language pathologists and specialist teachers.

Audio visual automatic speech recognition in vehicles

Acoustically, car cabins are extremely noisy and as a consequence, existing audio-only speech recognition systems, for voice-based control of vehicle functions such as the GPS based navigator, perform poorly. Audio-only speech recognition systems fail to make use of the visual modality of speech (eg: lip movements). As the visual modality is immune to acoustic noise, utilising this visual information in conjunction with an audio only speech recognition system has the potential to improve the accuracy of the system. The field of recognising speech using both auditory and visual inputs is known as Audio Visual Speech Recognition (AVSR). Continuous research in AVASR field has been ongoing for the past twenty-five years with notable progress being made. However, the practical deployment of AVASR systems for use in a variety of real-world applications has not yet emerged. The main reason is due to most research to date neglecting to address variabilities in the visual domain such as illumination and viewpoint in the design of the visual front-end of the AVSR system. In this paper we present an AVASR system in a real-world car environment using the AVICAR database [1], which is publicly available in-car database and we show that the use of visual speech conjunction with the audio modality is a better approach to improve the robustness and effectiveness of voice-only recognition systems in car cabin environments.

Towards improved speech recognition for resource poor languages

In recent times, the improved levels of accuracy obtained by Automatic Speech Recognition (ASR) technology has made it viable for use in a number of commercial products. Unfortunately, these types of applications are limited to only a few of the world’s languages, primarily because ASR development is reliant on the availability of large amounts of language specific resources. This motivates the need for techniques which reduce this language-specific, resource dependency. Ideally, these approaches should generalise across languages, thereby providing scope for rapid creation of ASR capabilities for resource poor languages. Cross Lingual ASR emerges as a means for addressing this need. Underpinning this approach is the observation that sound production is largely influenced by the physiological construction of the vocal tract, and accordingly, is human, and not language specific. As a result, a common inventory of sounds exists across languages; a property which is exploitable, as sounds from a resource poor, target language can be recognised using models trained on resource rich, source languages. One of the initial impediments to the commercial uptake of ASR technology was its fragility in more challenging environments, such as conversational telephone speech. Subsequent improvements in these environments has gained consumer confidence. Pragmatically, if cross lingual techniques are to considered a viable alternative when resources are limited, they need to perform under the same types of conditions. Accordingly, this thesis evaluates cross lingual techniques using two speech environments; clean read speech and conversational telephone speech. Languages used in evaluations are German, Mandarin, Japanese and Spanish. Results highlight that previously proposed approaches provide respectable results for simpler environments such as read speech, but degrade significantly when in the more taxing conversational environment. Two separate approaches for addressing this degradation are proposed. The first is based on deriving better target language lexical representation, in terms of the source language model set. The second, and ultimately more successful approach, focuses on improving the classification accuracy of context-dependent (CD) models, by catering for the adverse influence of languages specific phonotactic properties. Whilst the primary research goal in this thesis is directed towards improving cross lingual techniques, the catalyst for investigating its use was based on expressed interest from several organisations for an Indonesian ASR capability. In Indonesia alone, there are over 200 million speakers of some Malay variant, provides further impetus and commercial justification for speech related research on this language. Unfortunately, at the beginning of the candidature, limited research had been conducted on the Indonesian language in the field of speech science, and virtually no resources existed. This thesis details the investigative and development work dedicated towards obtaining an ASR system with a 10000 word recognition vocabulary for the Indonesian language.