Artificial Bandwidth Extension of Speech Signals using Neural Networks

Although mobile wideband telephony has been standardized for over 15 years, many countries still do not have a nationwide network with good coverage. As a result, many cellphone calls are still downgraded to narrowband telephony. The resulting loss of quality can be reduced by artificial bandwidth extension. There has been great progress in bandwidth extension in recent years due to the use of neural networks. The topic of this thesis is the enhancement of artificial bandwidth extension using neural networks. A special focus is given to hands-free calls in a car, where the risk is high that the wideband connection is lost due to the fast movement. The bandwidth of narrowband transmission is not only reduced towards higher frequencies above 3.5 kHz but also towards lower frequencies below 300 Hz. There are already methods that estimate the low-frequency components quite well, which will therefore not be covered in this thesis. In most bandwidth extension algorithms, the narrowband signal is initially separated into a spectral envelope and an excitation signal. Both parts are then extended separately in order to finally combine both parts again. While the extension of the excitation can be implemented using simple methods without reducing the speech quality compared to wideband speech, the estimation of the spectral envelope for frequencies above 3.5 kHz is not yet solved satisfyingly. Current bandwidth extension algorithms are just able to reduce the quality loss due to narrowband transmission by a maximum of 50% in most evaluations. In this work, a modification for an existing method for excitation extension is proposed which achieves slight improvements while not generating additional computational complexity. In order to enhance the wideband envelope estimation with neural networks, two modifications of the training process are proposed. On the one hand, the loss function is extended with a discriminative part to address the different characteristics of phoneme classes. On the other hand, by using a GAN (generative adversarial network) for the training phase, a second network is added temporarily to evaluate the quality of the estimation. The neural networks that were trained are compared in subjective and objective evaluations. A final listening test addressed the scenario of a hands-free call in a car, which was simulated acoustically. The quality loss caused by the missing high frequency components could be reduced by 60% with the proposed approach.Obwohl die mobile Breitbandtelefonie bereits seit über 15 Jahren standardisiert ist, gibt es oftmals noch kein flächendeckendes Netz mit einer guten Abdeckung. Das führt dazu, dass weiterhin viele Mobilfunkgespräche auf Schmalbandtelefonie heruntergestuft werden. Der damit einhergehende Qualitätsverlust kann mit künstlicher Bandbreitenerweiterung reduziert werden. Das Thema dieser Arbeit sind Methoden zur weiteren Verbesserungen der Qualität des erweiterten Sprachsignals mithilfe neuronaler Netze. Ein besonderer Fokus liegt auf der Freisprech-Telefonie im Auto, da dabei das Risiko besonders hoch ist, dass durch die schnelle Fortbewegung die Breitbandverbindung verloren geht. Bei der Schmalbandübertragung fehlen neben den hochfrequenten Anteilen (etwa 3.5–7 kHz) auch tiefe Frequenzen unterhalb von etwa 300 Hz. Diese tieffrequenten Anteile können mit bereits vorhandenen Methoden gut geschätzt werden und sind somit nicht Teil dieser Arbeit. In vielen Algorithmen zur Bandbreitenerweiterung wird das Schmalbandsignal zu Beginn in eine spektrale Einhüllende und ein Anregungssignal aufgeteilt. Beide Anteile werden dann separat erweitert und schließlich wieder zusammengeführt. Während die Erweiterung der Anregung nahezu ohne Qualitätsverlust durch einfache Methoden umgesetzt werden kann ist die Schätzung der spektralen Einhüllenden für Frequenzen über 3.5 kHz noch nicht zufriedenstellend gelöst. Mit aktuellen Methoden können im besten Fall nur etwa 50% der durch Schmalbandübertragung reduzierten Qualität zurückgewonnen werden. Für die Anregungserweiterung wird in dieser Arbeit eine Variation vorgestellt, die leichte Verbesserungen erzielt ohne dabei einen Mehraufwand in der Berechnung zu erzeugen. Für die Schätzung der Einhüllenden des Breitbandsignals mithilfe neuronaler Netze werden zwei Änderungen am Trainingsprozess vorgeschlagen. Einerseits wird die Kostenfunktion um einen diskriminativen Anteil erweitert, der das Netz besser zwischen verschiedenen Phonemen unterscheiden lässt. Andererseits wird als Architektur ein GAN (Generative adversarial network) verwendet, wofür in der Trainingsphase ein zweites Netz verwendet wird, das die Qualität der Schätzung bewertet. Die trainierten neuronale Netze wurden in subjektiven und objektiven Tests verglichen. Ein abschließender Hörtest diente zur Evaluierung des Freisprechens im Auto, welches akustisch simuliert wurde. Der Qualitätsverlust durch Wegfallen der hohen Frequenzanteile konnte dabei mit dem vorgeschlagenen Ansatz um etwa 60% reduziert werden

Glottal-synchronous speech processing

Glottal-synchronous speech processing is a field of speech science where the pseudoperiodicity of voiced speech is exploited. Traditionally, speech processing involves segmenting and processing short speech frames of predefined length; this may fail to exploit the inherent periodic structure of voiced speech which glottal-synchronous speech frames have the potential to harness. Glottal-synchronous frames are often derived from the glottal closure instants (GCIs) and glottal opening instants (GOIs). The SIGMA algorithm was developed for the detection of GCIs and GOIs from the Electroglottograph signal with a measured accuracy of up to 99.59%. For GCI and GOI detection from speech signals, the YAGA algorithm provides a measured accuracy of up to 99.84%. Multichannel speech-based approaches are shown to be more robust to reverberation than single-channel algorithms. The GCIs are applied to real-world applications including speech dereverberation, where SNR is improved by up to 5 dB, and to prosodic manipulation where the importance of voicing detection in glottal-synchronous algorithms is demonstrated by subjective testing. The GCIs are further exploited in a new area of data-driven speech modelling, providing new insights into speech production and a set of tools to aid deployment into real-world applications. The technique is shown to be applicable in areas of speech coding, identification and artificial bandwidth extension of telephone speec

Improving the robustness of CELP-like speech decoders using late-arrival packets information : application to G.729 standard in VoIP

L'utilisation de la voix sur Internet est une nouvelle tendance dans Ie secteur des télécommunications et de la réseautique. La paquetisation des données et de la voix est réalisée en utilisant Ie protocole Internet (IP). Plusieurs codecs existent pour convertir la voix codée en paquets. La voix codée est paquetisée et transmise sur Internet. À la réception, certains paquets sont soit perdus, endommages ou arrivent en retard. Ceci est cause par des contraintes telles que Ie délai («jitter»), la congestion et les erreurs de réseau. Ces contraintes dégradent la qualité de la voix. Puisque la transmission de la voix est en temps réel, Ie récepteur ne peut pas demander la retransmission de paquets perdus ou endommages car ceci va causer plus de délai. Au lieu de cela, des méthodes de récupération des paquets perdus (« concealment ») s'appliquent soit à l'émetteur soit au récepteur pour remplacer les paquets perdus ou endommages. Ce projet vise à implémenter une méthode innovatrice pour améliorer Ie temps de convergence suite a la perte de paquets au récepteur d'une application de Voix sur IP. La méthode a déjà été intégrée dans un codeur large-bande (AMR-WB) et a significativement amélioré la qualité de la voix en présence de <<jitter » dans Ie temps d'arrivée des trames au décodeur. Dans ce projet, la même méthode sera intégrée dans un codeur a bande étroite (ITU-T G.729) qui est largement utilise dans les applications de voix sur IP. Le codeur ITU-T G.729 défini des standards pour coder et décoder la voix a 8 kb/s en utilisant 1'algorithme CS-CELP (Conjugate Stmcture Algebraic Code-Excited Linear Prediction).Abstract: Voice over Internet applications is the new trend in telecommunications and networking industry today. Packetizing data/voice is done using the Internet protocol (IP). Various codecs exist to convert the raw voice data into packets. The coded and packetized speech is transmitted over the Internet. At the receiving end some packets are either lost, damaged or arrive late. This is due to constraints such as network delay (fitter), network congestion and network errors. These constraints degrade the quality of speech. Since voice transmission is in real-time, the receiver can not request the retransmission of lost or damaged packets as this will cause more delay. Instead, concealment methods are applied either at the transmitter side (coder-based) or at the receiver side (decoder-based) to replace these lost or late-arrival packets. This work attempts to implement a novel method for improving the recovery time of concealed speech The method has already been integrated in a wideband speech coder (AMR-WB) and significantly improved the quality of speech in the presence of jitter in the arrival time of speech frames at the decoder. In this work, the same method will be integrated in a narrowband speech coder (ITU-T G.729) that is widely used in VoIP applications. The ITUT G.729 coder defines the standards for coding and decoding speech at 8 kb/s using Conjugate Structure Algebraic Code-Excited Linear Prediction (CS-CELP) Algorithm

Coding Strategies for Cochlear Implants Under Adverse Environments

Cochlear implants are electronic prosthetic devices that restores partial hearing in patients with severe to profound hearing loss. Although most coding strategies have significantly improved the perception of speech in quite listening conditions, there remains limitations on speech perception under adverse environments such as in background noise, reverberation and band-limited channels, and we propose strategies that improve the intelligibility of speech transmitted over the telephone networks, reverberated speech and speech in the presence of background noise. For telephone processed speech, we propose to examine the effects of adding low-frequency and high- frequency information to the band-limited telephone speech. Four listening conditions were designed to simulate the receiving frequency characteristics of telephone handsets. Results indicated improvement in cochlear implant and bimodal listening when telephone speech was augmented with high frequency information and therefore this study provides support for design of algorithms to extend the bandwidth towards higher frequencies. The results also indicated added benefit from hearing aids for bimodal listeners in all four types of listening conditions. Speech understanding in acoustically reverberant environments is always a difficult task for hearing impaired listeners. Reverberated sounds consists of direct sound, early reflections and late reflections. Late reflections are known to be detrimental to speech intelligibility. In this study, we propose a reverberation suppression strategy based on spectral subtraction to suppress the reverberant energies from late reflections. Results from listening tests for two reverberant conditions (RT60 = 0.3s and 1.0s) indicated significant improvement when stimuli was processed with SS strategy. The proposed strategy operates with little to no prior information on the signal and the room characteristics and therefore, can potentially be implemented in real-time CI speech processors. For speech in background noise, we propose a mechanism underlying the contribution of harmonics to the benefit of electroacoustic stimulations in cochlear implants. The proposed strategy is based on harmonic modeling and uses synthesis driven approach to synthesize the harmonics in voiced segments of speech. Based on objective measures, results indicated improvement in speech quality. This study warrants further work into development of algorithms to regenerate harmonics of voiced segments in the presence of noise

Proceedings of the Second International Mobile Satellite Conference (IMSC 1990)

Presented here are the proceedings of the Second International Mobile Satellite Conference (IMSC), held June 17-20, 1990 in Ottawa, Canada. Topics covered include future mobile satellite communications concepts, aeronautical applications, modulation and coding, propagation and experimental systems, mobile terminal equipment, network architecture and control, regulatory and policy considerations, vehicle antennas, and speech compression

Analysis of Speech Recognition Techniques

Speech recognition has been an intregral part of human life acting as one of the five senses of human body, because of which application developed on the basis of speech recognition has high degree of acceptance. Here in this project we tried to analyse the different steps involved in artificial speech recognition by man-machine interface. The various steps we followed in speech recognition are feature extraction, distance calculation, dynamic time wrapping. We have tried to find out an approach which is both simple and efficient so that it can be utilised in embedded systems. After analysing the steps above we realised the process using small programs using MATLAB which is able to do small no. of isolated word recognition

Telephone speech enhancement for the hearing impaired

This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2009.Cataloged from PDF version of thesis report.Includes bibliographical references (page 48).Bony TasnimC. Z. MurshedB. Computer Science and Engineerin

Scalable Speech Coding for IP Networks

The emergence of Voice over Internet Protocol (VoIP) has posed new challenges to the development of speech codecs. The key issue of transporting real-time voice packet over IP networks is the lack of guarantee for reasonable speech quality due to packet delay or loss. Most of the widely used narrowband codecs depend on the Code Excited Linear Prediction (CELP) coding technique. The CELP technique utilizes the long-term prediction across the frame boundaries and therefore causes error propagation in the case of packet loss and need to transmit redundant information in order to mitigate the problem. The internet Low Bit-rate Codec (iLBC) employs the frame-independent coding and therefore inherently possesses high robustness to packet loss. However, the original iLBC lacks in some of the key features of speech codecs for IP networks: Rate flexibility, Scalability, and Wideband support. This dissertation presents novel scalable narrowband and wideband speech codecs for IP networks using the frame independent coding scheme based on the iLBC. The rate flexibility is added to the iLBC by employing the discrete cosine transform (DCT) and iii the scalable algebraic vector quantization (AVQ) and by allocating different number of bits to the AVQ. The bit-rate scalability is obtained by adding the enhancement layer to the core layer of the multi-rate iLBC. The enhancement layer encodes the weighted iLBC coding error in the modified DCT (MDCT) domain. The proposed wideband codec employs the bandwidth extension technique to extend the capabilities of existing narrowband codecs to provide wideband coding functionality. The wavelet transform is also used to further enhance the performance of the proposed codec. The performance evaluation results show that the proposed codec provides high robustness to packet loss and achieves equivalent or higher speech quality than state-of-the-art codecs under the clean channel condition