Motorola presents in collaboration with CNEL Introduction  Motivation: The limitation of traditional narrowband transmission channel  Advantage: Phone line frequency range: 300Hz- 3400Hz; Recovered frequency range: 20Hz-8000Hz  Goal: Increase the speech intelligibility and quality by adding artificial high frequency components  Basic Assumption: The high correlation between the low-frequency and high-frequency components of the same phonemes  Frequency fold  GMM algorithm Meena Ramani, Lingyun Gu, Kausthub Kale Aim Method Captions to be set in Times or Times New Roman or equivalent, italic, 18 to 24 points, to the length of the column in case a figure takes more than 2/3 of column width. Bandwidth Expansion Direction of arrival estimation & Beamforming Speech enhancement for cell phones Use psychoacoustic and auditory system knowledge to improve speech loudness and intelligibility Motivation Need for enhanced voice quality Complete mobility under noisy conditions Ability to identify different speakers in a conference call Direction Of Arrival (DOA) estimation Real time operation Constraints Physical constraints Low software and hardware complexity Good performance at all frequencies Increase the intelligibility of speech Differentiate speech source from noise source Overcome problems of signal distortion due to noise Prevent loss of accuracy due to room reverberations DOA Algorithms Spatial Correlation methods Delay and SumMinimum Variance Subspace decomposition methods MUSIC Multiple Signal Estimation Coherent MUSIC Root MUSIC ESPRIT Estimation of Signal parameters using rotational invariance DOA Requirements DOA Algorithm requirements Low computational intensity (FLOPS) High accuracy (Confidence Interval) High speed (Time taken) Easy to implement Work well at low SNRs Work well in a 2 microphone narrow baseline (4cm) system. DOA Method Equation for Implementation Delay and Sum Minimum Variance MUSIC Coherent MUSIC Root MUSIC ESPRIT Low FLOPS count Good Accuracy High Speed and good low SNR performance LPC analysis Excitation regeneration WB LPC synthesis HPF Features extraction Spectral envelope estimation 1:2LPF + with and Hamming window length20 ms LPC order(wideband)18 LPC order(narrowband)14 Spectral representationLPC cepstrum Mixture number (Q)128 VQ codebook size128 Bandwidth Extension of Telephone Speech Excitation Regeneration Spectral Envelope Regeneration Project Golden Voice ® Golden voice Plot comparing the MSE for the six different methods at different SNRs Comparison of FLOPS for the six different methods for 10dB SNR ESPRIT Tradeoff between Accuracy and Computational intensity Frequency Independent Beamformer Beamforming is the signal processing technique which operate on multiple sensor arrays Types of Beamforming Frequency Dependent Frequency Independent Conventional Beamformers are all frequency dependent. The few Frequency independent beamformers available work with large(512 microphone) array systems Novel approach The algorithm developed at CNEL works on a narrow baseline (4cm) 2 microphone system The results are superior to conventional techniques Speech with babble noise in the background Signal processed by the algorithm Speech with pink noise in the background Signal processed by the algorithm Improvements in SNRImprovement in Recognition Results Improvements in SNR for varying Noise DOA Performance comparison between Motorola's Noise suppressor and our algorithm Outperforms!