Audio bandwidth extension
226965585
On Filter Generalization for Music Bandwidth Extension Using Deep Neural Networks
In this paper, we address a subtopic of the broad domain of audio enhancement, namely musical audio bandwidth extension. We formulate the bandwidth extension problem using deep neural networks, where a band limited signal is provided as input to the network, with the goal of reconstructing a full bandwidth output. Our main contribution centers on the impact of the choice of low pass filter when training and subsequently testing the network. For two different state of the art deep architectures, ResNet and U Net, we demonstrate that when the training and testing filters are matched, improvements in signal to noise ratio (SNR) of up to 7 dB can be obtained. However, when these filters differ, the improvement falls considerably and under some training conditions results in a lower SNR than the band limited input. To circumvent this apparent overfitting to filter shape, we propose a data augmentation strategy which utilizes multiple low pass filters during training and leads to improved generalization to unseen filtering conditions at test time.
IEEE Journal of Selected Topics in Signal Processing
Serkan Sulun Matthew E P Davies
235771285
Bandwidth Extension is All You Need
Speech generation and enhancement have seen recent breakthroughs in quality thanks to deep learning. These methods typically operate at a limited sampling rate of 16 22kHz due to computational complexity and available datasets. This limitation imposes a gap between the output of such methods and that of high fidelity =44kHz) real world audio applications. This paper proposes a new bandwidth extension (BWE) method that expands 8 16kHz speech signals to 48kHz. The method is based on a feed forward WaveNet architecture trained with a GAN based deep feature loss. A mean opinion score (MOS) experiment shows significant improvement in quality over state of the art BWE methods. An AB test reveals that our 16 to 48kHz BWE is able to achieve fidelity that is typically indistinguishable from real high fidelity recordings. We use our method to enhance the output of recent speech generation and denoising methods, and experiments demonstrate significant improvement in sound quality over these baselines. We propose this as a general approach to narrow the gap between generated speech and recorded speech, without the need to adapt such methods to higher sampling rates.
ICASSP 2021 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Yunyun Wang Adam Finkelstein Zeyu Jin
229357871
Blind Bandwidth Extension of Speech based on LPCNet
A blind bandwidth extension is presented which improves the perceived quality of 4 kHz speech by artificially extending the speech's frequency range to 8 kHz. Based on the source filter model of the human speech production, the speech signal is decomposed into spectral envelope and excitation signal and each of them is extrapolated separately. With this decomposition, good perceptual quality can be achieved while keeping the computational complexity low. The focus of this work is in the generation of an excitation signal with and autoregressive model that calculates a distribution for each audio sample conditioned on previous samples. This is achieved with a deep neural network following the architecture of LPCNet [1].A listening test shows that it significantly improves the perceived quality of bandlimited speech. The system has an algorithmic delay of 30 ms and can be applied in state of the art speech and audio codecs.
2020 28th European Signal Processing Conference (EUSIPCO)
Konstantin Schmidt Bernd Edler
236513907
HIFI GAN 2: STUDIO QUALITY SPEECH ENHANCEMENT VIA GENERATIVE ADVERSARIAL NETWORKS CONDITIONED ON ACOUSTIC FEATURES
Modern speech content creation tasks such as podcasts, video voice overs, and audio books require studio quality audio with full bandwidth and balanced equalization (EQ) These goals pose a challenge for conventional speech enhancement methods, which typically focus on removing significant acoustic degradation such as noise and reverb so as to improve speech clarity and intelligibility. We present HiFi GAN 2, a waveform to waveform enhancement method that improves the quality of real world consumer grade recordings, with moderate noise, reverb and EQ distortion, to sound like studio recordings. HiFi GAN 2 has three components. First, given a noisy reverberant recording as input, a recurrent network predicts the acoustic features (MFCCs) of a clean signal. Second, given the same noisy input, and conditioned on the MFCCs output by the first network, a feed forward WaveNet (modeled via multidomain multi scale adversarial training) generates a clean 16kHz signal. Third, a pre trained bandwidth extension network generates the final 48kHz studio quality signal from the 16kHz output of the second network. The complete pipeline is trained via simulation of noise, reverb and EQ added to studio quality speech. Objective and subjective evaluations show that the proposed method outperforms state of the art baselines on both conventional denoising as well as joint dereverberation and denoising tasks. Listening tests also show that our method achieves close to studio quality on real world speech content (TED Talks and the VoxCeleb dataset)
Zeyu Jin Adam Finkelstein
233925976
Ultra Wide Bandwidth Fully Differential CMOS Opamp with a Novel Bandwidth Extension Technique for SoC Active Filter Applications
An ultra wide bandwidth fully differential two stage 65[Formula: see text]nm CMOS operational amplifier (Opamp) is presented, which uses a novel bandwidth extension technique called "pole duplication" This technique is based on relocating the dominant pole with the same location with a non dominant pole and adjusting 3 dB frequency and stability with a compensation network. Simulation results show that the proposed Opamp has 103[Formula: see text]MHz 3 dB bandwidth with a 2[Formula: see text]pF load capacitor. It consumes 9[Formula: see text]mA current from 1.2 V supply. Transition frequency of 2.4[Formula: see text]GHz and a gain of 29[Formula: see text]dB is accomplished. A 2[Formula: see text]pF load capacitance can be driven at a phase margin of [Formula: see text] The suggested pole duplication technique is used to achieve higher 3 dB cut off frequencies by adjusting the load capacitor. Fully differential two stage Opamp is presented, which uses a novel bandwidth extension technique, is suitable for SoC active filter applications with 40[Formula: see text][Formula: see text]m layout area and ultra wide 3 dB bandwidth.
Toprak Kayanselcuk Ertan Zencir
231589952
Single layer metasurface for ultra wideband polarization conversion: bandwidth extension via Fano resonance
In this paper, we propose a method of designing ultra wideband single layer metasurfaces for cross polarization conversion, via the introduction of Fano resonances. By adding sub branches onto the unit cell structure, the induced surface currents are disturbed, leading to coexistence of both bright and dark modes at higher frequencies. Due to the strong interaction between the two modes, Fano resonance can be produced. In this way, five resonances in all are produced by the single layer metasurface. The first four are conventional and are generated by electric and magnetic resonances, whereas the fifth one is caused by Fano resonance, which further extends the bandwidth. A prototype was designed, fabricated and measured to verify this method. Both the simulated and measured results show that a 1:4.4 bandwidth can be achieved for both x and y polarized waves, with almost all polarization conversion ratio (PCR) above 90% This method provides an effective alternative to metasurface bandwidth extension and can also be extended to higher bands such as THz and infrared frequencies.
Scientific reports
Zhongtao Zhang Jiafu Wang Xinmin Fu Yuxiang Jia Hongya Chen Mingde Feng Ruichao Zhu Shaobo Qu
235749118
Bandwidth Extension of Three Way Doherty Power Amplifier With Reactance Compensation Using Parallel Peaking Amplifiers
This paper presents a new methodology for designing a broadband three way Doherty power amplifier (DPA) which utilizes a reactance compensation generated by parallel peaking amplifiers to extend the bandwidth and improve the back off efficiency. By analyzing the load impedance and efficiency of the reactance compensated DPA, the optimal reactance at the output of the peaking amplifier required for bandwidth extension can be obtained. Then, a structure using two parallel peaking amplifiers is proposed to reduce the output reactance for the desired distribution. Using a \lambda _{0} /4 transmission line, a sufficiently large output reactance of the peaking branch can be realized at the combining point over a wider frequency band, which can compensate the effective load impedance of the carrier amplifier and improve its efficiency and bandwidth. A wideband three way DPA is designed and fabricated to verify the proposed method. Measurement results indicate that an efficiency of 50 53% at 10 dB output power back off and a saturated efficiency of 54 68% can be achieved over the frequency range from 1.6 to 2.7 GHz.
IEEE Access
Wa Kong Jing Xia Wence Zhang Xu Bao
236644516
A DC Ka Band 7 Bit Passive Attenuator With Capacitive Compensation Based Bandwidth Extension Technique in 55 nm CMOS
This article presents a 7 bit wideband passive attenuator with low insertion loss (IL) and high attenuation accuracy in 55 nm CMOS technology. The \pi type and bridge T type attenuation units utilize an effective capacitive compensation technique, whose bandwidth extension mechanism is detailed in a single unit pole zero analysis. The matching induced performance deterioration is investigated to minimize amplitude and phase errors at the chip level. The fabricated attenuator demonstrates a 32.4 dB attenuation range with a 0.255 dB resolution and a 3.5 8.4 dB IL from dc to 32 GHz. The measured root mean square (rms) amplitude and phase errors are below 0.32 dB and 5.33deg, respectively. The attenuator occupies a 0.054 mm2 core area and consumes negligible power.
IEEE Transactions on Microwave Theory and Techniques
Zijiang Zhang Yen-Cheng Kuan Qun Jane Gu
236296011
DWT DCT Based Data Hiding for Speech Bandwidth Extension
The limited narrowband frequency range, about 300 3400Hz, used in telephone network channels results in less intelligible and poor quality telephony speech. To address this drawback, a novel robust speech bandwidth extension using Discrete Wavelet Transform Discrete Cosine Transform Based Data Hiding is proposed. In this technique, the missing speech information is embedded in the narrowband speech signal. The embedded missing speech information is recovered steadily at the receiver end to generate a wideband speech of considerably better quality. The robustness of the proposed method to quantization and channel noises is confirmed by the mean square error test. The enhancement in the quality of reconstructed wideband speech of the proposed method over conventional methods is reasserted by subjective listening and objective tests.
Srinivas Koduri T Kumar
224819608
Real Time Speech Frequency Bandwidth Extension
In this paper we propose a lightweight model for frequency bandwidth extension of speech signals, increasing the sampling frequency from 8kHz to 16kHz while restoring the high frequency content to a level almost indistinguishable from the 16kHz ground truth. The model architecture is based on SEANet (Sound EnhAncement Network) a wave to wave fully convolutional model, which uses a combination of feature losses and adversarial losses to reconstruct an enhanced version of the input speech. In addition, we propose a variant of SEANet that can be deployed on device in streaming mode, achieving an architectural latency of 16ms. When profiled on a single core of a mobile CPU, processing one 16ms frame takes only 1.5ms. The low latency makes it viable for bi directional voice communication systems.
ICASSP 2021 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Yunpeng Li Marco Tagliasacchi Oleg Rybakov Victor Ungureanu Dominik Roblek