Abstract
Most systems for the transmission and storage of speech and audio signals are nowadays based on digital technology. For specific applications, e.g., wireless microphones for live concerts, however, operation constraints are defined which only analog technology could fulfill. The most critical and often contradictory constraints are a low algorithmic delay, a high perceived quality for speech as well as for audio signals at low bit rates and a low computational complexity. State-of-the-art standardized approaches for digital lossy source coding in general either have a high algorithmic delay or have been optimized for speech signals only and are not suitable for audio coding. The outcome of this thesis are novel approaches for the lossy compression of digital speech and audio signals with low algorithmic delay. The new concepts are principally based on combined linear prediction and vector quantization which is wellknown from state-of-the-art speech codecs. However, fundamental modifications of
the concepts known from speech coding are essential to achieve a low algorithmic delay and a low computational complexity as well as a high perceived speech and audio quality at low bit rates.
The developed approaches for low delay audio coding significantly outperform standardized audio codecs with a comparable algorithmic delay and bit rate, e.g., the ITU-T G.722 audio codec, in terms of a higher subjective quality for speech and particularly audio signals.
Most systems for the transmission and storage of speech and audio signals are nowadays based on digital technology. For specific applications, e.g., wireless microphones for live concerts, however, operation constraints are defined which only analog technology could fulfill. The most critical and often contradictory constraints are a low algorithmic delay, a high perceived quality for speech as well as for audio signals at low bit rates and a low computational complexity. State-of-the-art standardized approaches for digital lossy source coding in general either have a high algorithmic delay or have been optimized for speech signals only and are not suitable for audio coding. The outcome of this thesis are novel approaches for the lossy compression of digital speech and audio signals with low algorithmic delay. The new concepts are principally based on combined linear prediction and vector quantization which is wellknown from state-of-the-art speech codecs. However, fundamental modifications of
the concepts known from speech coding are essential to achieve a low algorithmic delay and a low computational complexity as well as a high perceived speech and audio quality at low bit rates.
The developed approaches for low delay audio coding significantly outperform standardized audio codecs with a comparable algorithmic delay and bit rate, e.g., the ITU-T G.722 audio codec, in terms of a higher subjective quality for speech and particularly audio signals.
