Employing Smart Logic to Spot Audio in Real Time on Deeply Embedded Systems

Abstract. Audio mining is currently the subject of several research efforts, especially because of its potential to speed up search for spoken words in audio recordings. This study explores a method for approaching the problem from the bottom. It proposes a framework based on smart logic, mainly fuzzy logic, and on an audio model applicable to any kind of audio recording, including music. Keywords: Audio mining, audio spotting, fuzzy logic, phone unit, spoken term detection, phonetic search, keyword-spotting Premises Audio is the most powerful information medium available because of peculiarities that fit well with the requirements of the emerging technology found in embedded systems. Such technology will be very pervasive in the next generation of computing and communication devices. Because of those devices' deep level of embedding, audio will be the preferred interaction medium. There are several reasons for this. Audio can embed much more information than any other analog medium. Not only does it represent semantic information; the same audio frame contains behavioral, environmental, psychological, and expressive information. Another important peculiarity of audio as information medium is that only audio one can be accessed in eyes-free or hands-free mode. This means that very simple human-to-machine interfaces (HMIs) could be employed in the next generation of embedded devices. Audio is a one-dimensional signal, storage and processing are simpler and less resource-hungry than for other signal-information media, such as video. This feature is very important in developing embedded devices, because storage and processing power are always limited resources. Researchers are very interested in using audio as interaction medium for text retrieval in spoken documents (conference speeches, broadcast news, etc.) to provide smart access to spoken audio and audio corpora, including music. Such research is targeted at several application areas, mainly spoken document retrieval, media monitoring, and personal entertainment

Employing Smart Logic to Spot Audio in Real Time on Deeply Embedded Systems

Part 5: Fuzzy SystemsInternational audienceAudio mining is currently the subject of several research efforts, especially because of its potential to speed up search for spoken words in audio recordings. This study explores a method for approaching the problem from the bottom. It proposes a framework based on smart logic, mainly fuzzy logic, and on an audio model applicable to any kind of audio recording, including music

Speech Signal Processing in Application of Soft Computing Methods

Cílem této diplomové práce je prozkoumat odvětví Soft Computingových metod v oblasti zpracování řečového signálu, nalézt vhodnou metodu pro potlačení šumu a tu následně použít v simulaci a praktické realizaci. Vybraná metoda bude popsána teoreticky i matematicky a její implementace bude použita pro potlačení okolního šumu z hlasového signálu pro ovládání chytré domácnosti Smart Home založené na sběrnicovém systému KNX. Hlasové řízení provozně technických funkcí tohoto komunikačního sběrnicového systému je předpokladem pro jednodušší správu domácnosti, vylučující jinak nutnou manuální manipulaci s ovládacím zařízením a to zejména pro seniory nebo postižené osoby. V domácnostech se ovšem nachází řada rušivých elementů, mezi které můžeme zařadit například šum domácích spotřebičů, nebo vlivy počasí, které mohou zapříčinit nefunkčnost tohoto ovládání a je tedy potřeba je odstranit. V dnešní době je k dispozici již množství filtrů schopných uspokojivě odstranit předem specifikovaný šum, avšak použití nelineárních adaptivních metod by mohlo tyto výsledky posunout na zcela jinou úroveň. Po úspěšné implementaci je nutné provést zhodnocení signálu, zda byla použitá metoda v potlačení šumu úspěšná.The aim of this diploma thesis is investigate the field of Soft Computing methods in Speech Signal Processing and find an appropriate method for noise suppression and use it in simulation and practical implementation. The chosen method will be theoretically and mathematically described and used in implementation to suppress the ambient noise from speech signal for controlling a Smart Home based on the KNX bus system. Voice control of the operational technical features of this communication bus system is a prerequisite for a simpler household management, eliminating otherwise necessary manual handling of the control device, especially for seniors or disabled persons. However, in households there are a number of disturbing elements, including for example the noise of household appliances or weather conditions that may cause this control to malfunction and noise need to be removed. Nowadays, a number of filters are already available to satisfactorily remove pre-specified noise, but the use of non-linear adaptive methods could shift this results to a completely different level. After successful implementation, it is necessary to evaluate the signal if the used noise suppression method has been successful.450 - Katedra kybernetiky a biomedicínského inženýrstvídobř