Rico Petrick

Robustness optimization of a speech interface for child-directed embedded language tutoring

This contribution describes the robustness evaluation and optimization steps for a speech interface which is suitable for embedded language tutoring with special focus on childrens speech. The baseline algorithms are derived from the pronunciation tutoring system AzAR directed to adult learners of German. The first prototype LiSA (2008) - directed to young children starting at 3 years - is currently evaluated and optimized, mainly addressing following issues: (a) the challenge of ASR-based pronunciation assessment for childrens speech, (b) the handling of noise and reverberation in an embedded application scenario, and (c) the extraction of additional information such as age or gender. The article summarizes evaluation results of the speech recognizer in laboratory and real-world room environment.

The Acoustic Front-End in Scenarios of Interaction Research

The paper is concerning some problems which are posed by the growing interest in social interaction research as far as they can be solved by engineers in acoustics and speech technology. Firstly the importance of nonverbal and paraverbal modalities in two prototypical scenarios are discussed: face-to-face interactions in psychotherapeutic consulting and side-by-side interactions of children cooperating in a computer game. Some challenges in processing signals are stated with respect to both scenarios. The following technologies of acoustic signal processing are discussed: (a) analysis of the influence of the room impulse response to the recognition rate, (b) adaptive two-channel microphone, (c) localization and separation of sound sources in rooms, and (d) single-channel noise suppression.

Verbkey - A Single-Chip Speech Control for the Automobile Environment

The article deals with a novel speech recognizer technology which has the potential to overcome some problems of in-car speech control. The verbKEY recognizer bases on the Associative-Dynamic (ASD) algorithm which differs from established techniques as HMM or DTW. The speech recognition technology is designed to run on a 16 bit, fixed point DSP platform. It enables high recognition performance and robustness. At the same time, it is highly cost efficient due to its low memory consumption and its less calculation complexity. Typical applications such as dialling, word spotting or menu structures for the device control are processed by the continuous, real-time recognition engine with an accuracy higher 98% for a 20 words vocabulary. The article describes a hardware prototype for command & control applications and the measures taken to improve the robustness against environmental noises. Finally, the authors discuss some ergonomic aspects to obtain a higher level of traffic safety.

Towards Minimally Invasive Velar State Detection in Normal and Silent Speech.

We present a portable minimally invasive system to determine the state of the velum (raised or lowered) at a sampling rate of 40 Hz that works both during normal and silent speech. The system consists of a small capsule containing a miniature loudspeaker and a miniature microphone. The capsule is inserted into one nostril by about 10 mm. The loudspeaker emits chirps with a power band from 12-24 kHz into the nostril and the microphone records the signal reflected from the nasal cavity. The chirp response differs between raised and lowered velar positions, because the velar position determines the shape of the nasal cavity in the posterior part and hence its acoustic behaviour. Reference chirp responses for raised and lowered velar positions in combination with a spectral distance measure are used to infer the state of the velum. Here we discuss critical design aspects of the system and outline future improvements. Possible applications of the device include the detection of the velar state during silent speech recognition, medical assessment of velar mobility and speech production research.