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.

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.

Identifying reliable, valid markers of authorship: a response to Chaski

In response to Chaski’s article (published in this volume) an examination is made of the methodological understanding necessary to identify dependable markers for forensic (and general) authorship attribution work. This examination concentrates on three methodological areas of concern which researchers intending to identify markers of authorship must address. These areas are sampling linguistic data, establishing the reliability of authorship markers and establishing the validity of authorship markers. It is suggested that the complexity of sampling problems in linguistic data is often underestimated and that theoretical issues in this area are both difficult and unresolved. It is further argued that the concepts of reliability and validity must be well understood and accounted for in any attempts to identify authorship markers and that largely this is not done. Finally, Principal Component Analysis is identified as an alternative approach which avoids some of the methodological problems inherent in identifying reliable, valid markers of authorship.

Statistical study of talk spurts and silence lengths with relation to various languages and speakers for advanced silence suppression in Next Generation Wireless Communication Devices

As wireless network technologies evolve towards an All-IP framework, Next Generation Wireless Communication Devices demand better use of spectral resources by employing advanced techniques of silence suppression. This paper presents an analysis of VoIP call data and compares the statistical results based on observed patterns of talk spurts and silence lengths to those achieved by a modified on-off voice model for silence suppression in wireless networks. As talk spurts and silence lengths are sensitive to varying word lengths, temporal structure and other prosodic aspects of speech, the impact of the use of various languages, dialects and gender of speakers on these results is also assessed.

The discourse of biology lectures : aspects of its mode and text structure

The present thesis investigates mode related aspects in biology lecture discourse and attempts to identify the position of this variety along the spontaneous spoken versus planned written language continuum. Nine lectures (of 43,000 words) consisting of three sets of three lectures each, given by the three lecturers at Aston University, make up the corpus. The indeterminacy of the results obtained from the investigation of grammatical complexity as measured in subordination motivates the need to take the analysis beyond sentence level to the study of mode related aspects in the use of sentence-initial connectives, sub-topic shifting and paraphrase. It is found that biology lecture discourse combines features typical of speech and writing at sentence as well as discourse level: thus, subordination is more used than co-ordination, but one degree complexity sentence is favoured; some sentence initial connectives are only found in uses typical of spoken language but sub-topic shift signalling (generally introduced by a connective) typical of planned written language is a major feature of the lectures; syntactic and lexical revision and repetition, interrupted structures are found in the sub-topic shift signalling utterance and paraphrase, but the text is also amenable to analysis into sentence like units. On the other hand, it is also found that: (1) while there are some differences in the use of a given feature, inter-speaker variation is on the whole not significant; (2) mode related aspects are often motivated by the didactic function of the variety; and (3) the structuring of the text follows a sequencing whose boundaries are marked by sub-topic shifting and the summary paraphrase. This study enables us to draw four theoretical conclusions: (1) mode related aspects cannot be approached as a simple dichotomy since a combination of aspects of both speech and writing are found in a given feature. It is necessary to go to the level of textual features to identify mode related aspects; (2) homogeneity is dominant in this sample of lectures which suggests that there is a high level of standardization in this variety; (3) the didactic function of the variety is manifested in some mode related aspects; (4) the features studied play a role in the structuring of the text.

A linguistic study of interview and conversation

The present thesis focuses on the overall structure of the language of two types of Speech Exchange Systems (SES) : Interview (INT) and Conversation (CON). The linguistic structure of INT and CON are quantitatively investigated on three different but interrelated levels of analysis : Lexis, Syntax and Information Structure. The corpus of data 1n vest1gated for the project consists of eight sessions of pairs of conversants in carefully planned interviews followed by unplanned, surreptitiously recorded conversational encounters of the same pairs of speakers. The data comprise a total of approximately 15.200 words of INT talk and of about 19.200 words in CON. Taking account of the debatable assumption that the language of SES might be complex on certain linguistic levels (e.g. syntax) (Halliday 1979) and might be simple on others (e.g. lexis) in comparison to written discourse, the thesis sets out to investigate this complexity using a statistical approach to the computation of the structures recurrent in the language of INT and CON. The findings indicate clearly the presence of linguistic complexity in both types. They also show the language of INT to be slightly more syntactically and lexically complex than that of CON. Lexical density seems to be relatively high in both types of spoken discourse. The language of INT seems to be more complex than that of CON on the level of information structure too. This is manifested in the greater use of Inferable and other linguistically complex entities of discourse. Halliday's suggestion that the language of SES is syntactically complex is confirmed but not the one that the more casual the conversation is the more syntactically complex it becomes. The results of the analysis point to the general conclusion that the linguistic complexity of types of SES is not only in the high recurrence of syntactic structures, but also in the combination of these features with each other and with other linguistic and extralinguistic features. The linguistic analysis of the language of SES can be useful in understanding and pinpointing the intricacies of spoken discourse in general and will help discourse analysts and applied linguists in exploiting it both for theoretical and pedagogical purposes.

A speech analysis system for use in educational research

This thesis describes work undertaken in order to fulfil a need experienced in the Department of Educational Enquiry at the University of Aston in Birmingham for speech analysis facilities suitable for use in teaching and research work within the Department. The hardware and software developed during the research project provides displays of speech fundamental frequency and intensity in real time. The system is suitable for the provision of visual feedback of these parameters of a subject's speech in a learning situation, and overcomes the inadequacies of equipment currently used for this task in that it provides a clear indication of fundamental frequency contours as the subject is speaking. The thesis considers the use of such equipment in several related fields, and the approaches that have been reported to one of the major problems of speech analysis, namely pitch-period estimation. A number of different systems are described, and their suitability for the present purposes is discussed. Finally, a novel method of pitch-period estimation is developed, and a speech analysis system incorporating this method is described. Comparison is made between the results produced by this system and those produced by a conventional speech spectrograph.

Speech recognition use in healthcare applications

Speech recognition technology is regarded as a key enabler for increasing the usability of applications deployed on mobile devices -- devices which are becoming increasingly prevalent in modern hospital-based healthcare. Although the use of speech recognition is not new to the hospital-based healthcare domain, its use with mobile devices has thus far been limited. This paper presents the results of a literature review we conducted in order to observe the manner in which speech recognition technology has been used in hospital-based healthcare and to gain an understanding of how this technology is being evaluated, in terms of its dependability and reliability, in healthcare settings. Our intent is that this review will help identify scope for future uses of speech recognition technologies in the healthcare domain, as well as to identify implications for the meaningful evaluation of such technologies given the specific context of use.

Semantic sentiment analysis of Twitter

Sentiment analysis over Twitter offer organisations a fast and effective way to monitor the publics' feelings towards their brand, business, directors, etc. A wide range of features and methods for training sentiment classifiers for Twitter datasets have been researched in recent years with varying results. In this paper, we introduce a novel approach of adding semantics as additional features into the training set for sentiment analysis. For each extracted entity (e.g. iPhone) from tweets, we add its semantic concept (e.g. Apple product) as an additional feature, and measure the correlation of the representative concept with negative/positive sentiment. We apply this approach to predict sentiment for three different Twitter datasets. Our results show an average increase of F harmonic accuracy score for identifying both negative and positive sentiment of around 6.5% and 4.8% over the baselines of unigrams and part-of-speech features respectively. We also compare against an approach based on sentiment-bearing topic analysis, and find that semantic features produce better Recall and F score when classifying negative sentiment, and better Precision with lower Recall and F score in positive sentiment classification.

Classroom implications of recent research into literacy development: from predictors to assessment

We outline how research into predictors of literacy underpins the development of increasingly accurate and informative assessments. We report three studies that emphasize the crucial role of speech and auditory skills on literacy development throughout primary and secondary school. Our first study addresses the effects of early childhood middle ear infections, the potential consequences for speech processing difficulties and the impact on early literacy development. Our second study outlines how speech and auditory skills are crucially related to early literacy in normally developing readers, whereas other skills such as motor, memory and IQ are only indirectly related. Our third study outlines the on-going impact of phonological awareness on reading and wider academic achievement in secondary-school pupils. Finally, we outline how teachers can use the current research to inform them about which assessments to conduct, and how to interpret the results. Copyright © 2008 John Wiley & Sons, Ltd.

The question of question types in police interviews:a review of the literature from a psychological and linguistic perspective

The past two decades has seen a plethora of papers and academic research conducted on investigative interviews with victims, witnesses and suspected offenders, with a particular focus on questioning techniques and typologies. However, despite this research, there still remain significant discrepancies amongst academic researchers and practitioners over how best to describe types of questions. This article considers the available literature relating to interviews with children and adults from both a psychological and linguistic perspective. In particular, we examine how different types of questions are described, and explore the discrepancies between competing definitions. © 2010, equinox publishing.

Speech recognition use in healthcare applications

Speech recognition technology is regarded as a key enabler for increasing the usability of applications deployed on mobile devices -- devices which are becoming increasingly prevalent in modern hospital-based healthcare. Although the use of speech recognition is not new to the hospital-based healthcare domain, its use with mobile devices has thus far been limited. This paper presents the results of a literature review we conducted in order to observe the manner in which speech recognition technology has been used in hospital-based healthcare and to gain an understanding of how this technology is being evaluated, in terms of its dependability and reliability, in healthcare settings. Our intent is that this review will help identify scope for future uses of speech recognition technologies in the healthcare domain, as well as to identify implications for the meaningful evaluation of such technologies given the specific context of use.