Daniela Braga

Impact of Age in ASR for the Elderly: Preliminary Experiments in European Portuguese

Standard automatic speech recognition (ASR) systems use acoustic models typically trained with speech of young adult speakers. Ageing is known to alter speech production in ways that require ASR systems to be adapted, in particular at the level of acoustic modeling. This paper reports ASR experiments that illustrate the impact of speaker age on speech recognition performance. A large read speech corpus in European Portuguese allowed us to measure statistically significant performance differences among age groups ranging from 60- to 90-year-old speakers. An increase of 41% relative (11.9% absolute) in word error rate was observed between 60-65-year-old and 81-86-year-old speakers. This paper also reports experiments on retraining acoustic models (AMs), further illustrating the impact of ageing on ASR performance. Differentiated gains were observed depending on the age range of the adaptation data use to retrain the acoustic models.

A rule-based grapheme-to-phone converter for tts systems in european portuguese

In this paper, a linguistically rule-based grapheme-to-phone (G2P) transcription algorithm is described for European Portuguese. A complete set of phonological and phonetic transcription rules regarding the European Portuguese standard variety is presented. This algorithm was implemented and tested by using online newspaper articles. The obtained experimental results gave rise to 98.80% of accuracy rate. Future developments in order to increase this value are foreseen. Our purpose with this work is to develop a module/ tool that can improve synthetic speech naturalness in European Portuguese. Other applications of this system can be expected like language teaching/learning. These results, together with our perspectives of future improvements, have proved the dramatic importance of linguistic knowledge on the development of Text-to-Speech systems (TTS).

AgeCI: HCI and Age Diversity

We present an overview of recent works in which age is an important driving factor for Human-Computer Interaction design and development. These serve as starting grounds to discuss current practices and highlight challenges that might serve as beacons for future research in the field.

On the development of an automatic voice pleasantness classification and intensity estimation system

In the last few years, the number of systems and devices that use voice based interaction has grown significantly. For a continued use of these systems, the interface must be reliable and pleasant in order to provide an optimal user experience. However there are currently very few studies that try to evaluate how pleasant is a voice from a perceptual point of view when the final application is a speech based interface. In this paper we present an objective definition for voice pleasantness based on the composition of a representative feature subset and a new automatic voice pleasantness classification and intensity estimation system. Our study is based on a database composed by European Portuguese female voices but the methodology can be extended to male voices or to other languages. In the objective performance evaluation the system achieved a 9.1% error rate for voice pleasantness classification and a 15.7% error rate for voice pleasantness intensity estimation.

Workshops Held at the First AAAI Conference on Human Computation and Crowdsourcing: A Report

The first AAAI Conference on Human Computation and Crowdsourcing (HCOMP-2013) was be held November 6-9, 2013 in Palm Springs, California. Three workshops took place on Saturday, November 9th: Crowdsourcing at Scale (full day), Human and Machine Learning in Games (full day) and Scaling Speech, Language Understanding and Dialogue through Crowdsourcing (half day). This report summarizes the activities of those three events.

Evaluating Voice Quality and Speech Synthesis Using Crowdsourcing

One of the key aspects of creating high quality synthetic speech is the validation process. Establishing validation processes that are reliable and scalable is challenging. Today, the maturity of the crowdsourcing infrastructure along with better techniques for validating the data gathered through crowdsourcing have made it possible to perform reliable speech synthesis validation at a larger scale. In this paper, we present a study of voice quality evaluation using the crowdsourcing platform. We investigate voice gender preference across eight locales for three typical TTS scenarios. We also examine to which degree speaker adaptation can carry over certain voice qualities, such as mood, of the target speaker to the adapted TTS. Based on an existing full TTS font, adaptation is carried out on a smaller amount of speech data from a target speaker. Finally, we show how crowdsourcing contributes to objective assessment when dealing with voice preference in voice talent selection.

Study of Abrasion Resistance of Steels by Micro-Scale Tests

Steels continue to have a preponderant role in mechanical components under all type of wear solicitations namely, abrasion. The ability of micro-scale abrasion test for evaluating the properties of bulk materials has been widely demonstrated. However, only recently this technique was especially developed to characterize thin-coated materials. This study presents results obtained in micro-scale abrasion tests performed on different low and high alloy steels. These steel samples underwent thermal and chemical (nitriding) treatments with the aim of enhancing their surface hardness. Nitriding parameters were varied so as to obtain different structures (with and without formation of a “white layer” of iron nitrides (ε-Fe2-3N or γ’-Fe4N compound layer). Test conditions such as normal load and concentration of the abrasive medium (SiC particles in distilled water) were changed in order to obtain a 2 or 3 body wear contact type. Results obtained allowed to compare the specific wear rate ks for the different steels and treatments tested as well as to relate the influence of surface hardness and test parameters on the wear mechanisms.

Giving Voices to Multimodal Applications

The use of speech interaction is important and useful in a wide range of applications. It is a natural way of interaction and it is easy to use by people in general. The development of speech enabled applications is a big challenge that increases if several languages are required, a common scenario, for example, in Europe. Tackling this challenge requires the proposal of methods and tools that foster easier deployment of speech features, harnessing developers with versatile means to include speech interaction in their applications. Besides, only a reduced variety of voices are available (sometimes only one per language) which raises problems regarding the fulfillment of user preferences and hinders a deeper exploration regarding voices’ adequacy to specific applications and users.

Kalman tracking linear predictor for vowel intelligibility enhancement on european portuguese HMM based speech synthesis

The recent developments on Hidden Markov Models (HMM) based speech synthesis showed that this is a promising technology fully capable of competing with other established techniques. However some issues still lack a solution. Several authors report an over-smoothing phenomenon on both time and frequencies which decreases naturalness and sometimes intelligibility. In this work we present a new vowel intelligibility enhancement algorithm that uses a discrete Kalman filter (DKF) for tracking frame based parameters. The inter-frame correlations are modelled by an autoregressive structure which provides an underlying time frame dependency and can improve time-frequency resolution. The systems performance has been evaluated using objective and subjective tests and the proposed methodology has led to improved results.

On the use of prosodic labelling in corpus-based linguistic studies of spontaneous speech

This paper addresses the construction of a spontaneous speech corpus in European Portuguese (hereafter EP), the corpus is presented and a prosodic labeling scheme that is here proposed is explained. The objective of this work is to provide a tool for linguistic analysis suitable to several research topics, which have speech and dialogue as objects. The main features considered in the database will be described and justified. Methodological problems and some observed prosodic and pragmatic related phenomena deriving from the labeling of the speech signal are also presented. a discussion is done about some applications on pragmatic studies, speech synthesis and prosodic phonology. Our purpose is to make this work available to scientific community, since there isn’t any other database of this kind informatically available for EP.