The adaptive multirate wideband speech codec (AMR-WB)

By B. Bessette, R. Salami, R. Lefebvre, M. Jelinek, J. Rotola-Pukkila, J. Vainio, H. Mikkola, Kari Järvinen. 2002

348 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Computer Vision and Pattern Recognition, Speech & Audio, Signal Processing

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In Computer Vision and Pattern Recognition

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Citations in the corpus

SoundStream: An End-to-End Neural Audio Codec (2021, methodology): “It is replacing AMR-WB [60] and retains full backward operability.”
Audiodec: An Open-Source Streaming High-Fidelity Neural Audio Codec (2023, neutral): “Modern parametric audio codecs [9–11] usually achieve acceptable reconstruction quality with 16 kHz or higher sampling rate audio signals as a consequence of the advanced transmission techniques.”
Cascaded Cross-Module Residual Learning towards Lightweight End-to-End Speech Coding (2019, methodology): “Therefore, for the subjective quality, we perform MUSHRA tests [31] to show that CMRL with an LPC residual input works better than AMR-WB and OPUS at high bitrates.”
End-To-End Optimized Speech Coding with Deep Neural Networks (2017, background): “Essentially all modern compression standards are handdesigned, including the most prominent wideband speech coder: AMR-WB [1].”
Improving Opus Low Bit Rate Quality with Neural Speech Synthesis (2019, methodology): “This opens the door to improving other existing speech coders, such as AMR-WB [7], extending their life without breaking compatibility.”
High-quality Speech Coding with Sample RNN (2018, methodology): “We benchmark our resulting speech coding scheme against AMR-WB [9] at 23.”
Adaptive Multi-rate Wideband Speech Codec Based on CELP Algorithm: Architectural Study, Implementation & Performance Analysis (2012, methodology): “The above codec modes are derived from ETSI standardization in 2001 [6].”
Neural Feature Predictor and Discriminative Residual Coding for Low-Bitrate Speech Coding (2022, background): “It has been used in various communication and entertainment applications after standardization [1, 2] or open-sourcing [3].”
Rate Distribution Between Model and Signal (2007, background): “Table 1 shows bit allocations used in the adaptive-multirate wide-band (AMR-WB) speech coder [7].”
Robust Low Rate Speech Coding Based on Cloned Networks and Wavenet (2020, background): “However, compared to parametric coding, waveform coding requires a rate that typically is an order of magnitude larger, e.g., compare [7,8] to the adaptive multi-rate wideband (AMR-WB) coder [12], standardized as ITU-T G722.”
Source Coding of Audio Signals with a Generative Model (2020, methodology): “[22] B. Bessette, R. Salami, R. Lefebvre, M. Jelinek, J. RotolaPukkila, J. Vainio, H. Mikkola, and K. Jarvinen, “The adaptive multirate wideband speech codec (AMR-WB),” IEEE Transactions on Speech and Audio Processing, vol. 10, no. 8, pp. 620–636, Nov 2002.”
MPEG Unified Speech and Audio Coding-The ISO/MPEG Standard for High-Efficiency Audio Coding of All C (2012, methodology): “AMR-WB+ Speech coding schemes, such as AMR-WB [4, 5], rely on a source model motivated by the mechanism of human speech production.”