Journal
INFORMATICA
Volume 28, Issue 2, Pages 403-414Publisher
INST MATHEMATICS & INFORMATICS
DOI: 10.15388/Informatica.2017.135
Keywords
speech codec; algebraic code-excited linear-prediction (ACELP); algebraic codebook search; depth-first tree search; VoIP
Funding
- Ministry of Science and Technology, Taiwan, Republic of China [MOST 104-2221-E-167-025]
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An adaptive multi-rate wideband (AMR-WB) speech codec with a sampling rate of 16 kHz is known as one of the speech codecs employed in handheld devices that support 4G mobile communication systems. When applied to smartphones, it provides a superior speech quality relative to conventional speech codecs. Nonetheless, a major disadvantage is that an algebraic code book search occupies a significant computational load in an AMR-WB encoder. In other words, the high computational complexity accounts for the high power consumption on a smartphone battery. This paper presents an improved version of depth-first tree search (DF) algorithm as a means to considerably reduce the complexity of an algebraic codebook search in an AMR-WB speech codec. This proposed search algorithm firstly involves the choice of a specified number of candidate pulses according to a pulse contribution ranking. Subsequently, a DF search is performed on the candidate pulses for a set of best pulses. Consequently, the target of the search and computational complexity reduction can be reached as expected. With a well maintained speech quality, this proposal demonstrates a search performance superiority over a DF and a global pulse replacement approach. Furthermore, with DF as a benchmark, a computational load reduction above 73% is reached in all coding modes.
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