arXiv subjects

Haibin Wu

Publications and source records attributed to Haibin Wu.

At least 91 records · Page 5Linked to original sources

arXiv2022

The CUHK-TENCENT speaker diarization system for the ICASSP 2022 multi-channel multi-party meeting transcription challenge

This paper describes our speaker diarization system submitted to the Multi-channel Multi-party Meeting Transcription (M2MeT) challenge, where Mandarin meeting data were recorded in multi-channel format for diarization and automatic speech recognition (ASR) tasks. In these meeting scenarios, the uncertainty of the speaker number and the high ratio of overlapped speech present great challenges for diarization. Based on the assumption that there is valuable complementary information between acoustic features, spatial-related and speaker-related features, we propose a multi-level feature fusion mechanism based target-speaker voice activity detection (FFM-TS-VAD) system to improve the performance of the conventional TS-VAD system. Furthermore, we propose a data augmentation method during training to improve the system robustness when the angular difference between two speakers is relatively small. We provide comparisons for different sub-systems we used in M2MeT challenge. Our submission is a fusion of several sub-systems and ranks second in the diarization task.

eess.AS↗

arXiv2021

Multipolar Fermi-surface deformation in a Rydberg-dressed Fermi gas with long-range anisotropic interactions

We study theoretically the deformation of the Fermi surface (FS) of a three-dimensional gas of Rydberg-dressed $^6$Li atoms. The laser dressing to high-lying Rydberg $D$ states results in angle-dependent soft-core-shaped interactions whose anisotropy is described by multiple spherical harmonics. We show that this can drastically modify the shape of the FS and that its deformation depends on the interplay between the Fermi momentum $k_F$ and the reciprocal momentum $\bar{k}$ corresponding to the characteristic soft-core radius of the dressing-induced potential. When $k_F< \bar{k}$, the dressed interaction stretches a spherical FS into an ellipsoid. When $k_F\gtrsim \bar{k}$, complex deformations are encountered which exhibit multipolar characteristics. We analyze the formation of Cooper pairs around the deformed FS and show that they occupy large orbital angular momentum states ($p$, $f$, and $h$ wave) coherently. Our study demonstrates that Rydberg dressing to high angular momentum states may pave a route toward the investigation of unconventional Fermi gases and multiwave superconductivity.

cond-mat.quant-gas↗

arXiv2021

Realization of a coupled-mode heat engine with cavity-mediated nanoresonators

We report an experimental demonstration of a coupled-mode heat engine in a two-membrane-in-the-middle cavity optomechanical system. The normal mode of the cavity-mediated strongly coupled nanoresonators is utilized as the working medium and an Otto cycle is realized by extracting work between two phononic thermal reservoirs. The heat engine performance is characterized in both normal mode and bare mode pictures, which reveals that the correlation of two membranes plays a significant role during the thermodynamic cycle. Moreover, a straight-twin nanomechanical engine is implemented by engineering the normal modes and operating two cylinders out-of-phase. Our results demonstrate an essential class of heat engine for the first time in cavity optomechanical systems and provide a novel platform for investigating heat engines of interacting subsystems in small scales with controllability and scalability.

quant-ph↗

arXiv2021

Dissipative coupling induced phonon lasing with anti-parity-time symmetry

Phonon lasers, as the counterpart of photonic lasers, have been intensively studied in a large variety of systems, however, (all) most of them are based on the directly coherent pumping. Intuitively, dissipation is an unfavorable factor for gain in a laser. Here we demonstrate a novel mechanism of phonon lasing from the dissipative coupling in a multimode optomechanical system. By precisely engineering the dissipations of two membranes and tuning the intensity modulation of the cavity light, the two-membrane-in-the-middle system shows anti-parity-time (anti-PT) symmetry and the cavity mediated interaction between two nanomechanical resonators becomes purely dissipative. The level attraction and damping repulsion are clearly exhibited as the signature of dissipative coupling. After the exceptional point, a non-Hermitian phase transition, where eigenvalues and the corresponding eigenmodes coalesce, two phonon modes are simultaneously excited into the self-sustained oscillation regime by increasing the interaction strength over a critical value (threshold). In distinct contrast to conventional phonon lasers, the measurement of the second-order phonon correlation reveals the oscillatory and biexponential phases in the nonlasing regime as well as the coherence phase in the lasing regime. Our study provides a new method to study phonon lasers in a non-Hermitian open system and could be applied to a wide range of disciplines, including optics, acoustics, and quantum many-body physics.

physics.optics↗

arXiv2021

Voting for the right answer: Adversarial defense for speaker verification

Automatic speaker verification (ASV) is a well developed technology for biometric identification, and has been ubiquitous implemented in security-critic applications, such as banking and access control. However, previous works have shown that ASV is under the radar of adversarial attacks, which are very similar to their original counterparts from human's perception, yet will manipulate the ASV render wrong prediction. Due to the very late emergence of adversarial attacks for ASV, effective countermeasures against them are limited. Given that the security of ASV is of high priority, in this work, we propose the idea of "voting for the right answer" to prevent risky decisions of ASV in blind spot areas, by employing random sampling and voting. Experimental results show that our proposed method improves the robustness against both the limited-knowledge attackers by pulling the adversarial samples out of the blind spots, and the perfect-knowledge attackers by introducing randomness and increasing the attackers' budgets.

cs.LG↗

arXiv2021

Tackling Variabilities in Autonomous Driving

The state-of-the-art driving automation system demands extreme computational resources to meet rigorous accuracy and latency requirements. Though emerging driving automation computing platforms are based on ASIC to provide better performance and power guarantee, building such an accelerator-based computing platform for driving automation still present challenges. First, the workloads mix and performance requirements exposed to driving automation system present significant variability. Second, with more cameras/sensors integrated in a future fully autonomous driving vehicle, a heterogeneous multi-accelerator architecture substrate is needed that requires a design space exploration for a new form of parallelism. In this work, we aim to extensively explore the above system design challenges and these challenges motivate us to propose a comprehensive framework that synergistically handles the heterogeneous hardware accelerator design principles, system design criteria, and task scheduling mechanism. Specifically, we propose a novel heterogeneous multi-core AI accelerator (HMAI) to provide the hardware substrate for the driving automation tasks with variability. We also define system design criteria to better utilize hardware resources and achieve increased throughput while satisfying the performance and energy restrictions. Finally, we propose a deep reinforcement learning (RL)-based task scheduling mechanism FlexAI, to resolve task mapping issue. Experimental results show that with FlexAI scheduling, basically 100% tasks in each driving route can be processed by HMAI within their required period to ensure safety, and FlexAI can also maximally reduce the breaking distance up to 96% as compared to typical heuristics and guided random-search-based algorithms.

cs.AR↗

arXiv2021

QR-MIX: Distributional Value Function Factorisation for Cooperative Multi-Agent Reinforcement Learning

In Cooperative Multi-Agent Reinforcement Learning (MARL) and under the setting of Centralized Training with Decentralized Execution (CTDE), agents observe and interact with their environment locally and independently. With local observation and random sampling, the randomness in rewards and observations leads to randomness in long-term returns. Existing methods such as Value Decomposition Network (VDN) and QMIX estimate the value of long-term returns as a scalar that does not contain the information of randomness. Our proposed model QR-MIX introduces quantile regression, modeling joint state-action values as a distribution, combining QMIX with Implicit Quantile Network (IQN). However, the monotonicity in QMIX limits the expression of joint state-action value distribution and may lead to incorrect estimation results in non-monotonic cases. Therefore, we proposed a flexible loss function to approximate the monotonicity found in QMIX. Our model is not only more tolerant of the randomness of returns, but also more tolerant of the randomness of monotonic constraints. The experimental results demonstrate that QR-MIX outperforms the previous state-of-the-art method QMIX in the StarCraft Multi-Agent Challenge (SMAC) environment.

cs.LG↗

arXiv2021

Adversarial defense for automatic speaker verification by cascaded self-supervised learning models

Automatic speaker verification (ASV) is one of the core technologies in biometric identification. With the ubiquitous usage of ASV systems in safety-critical applications, more and more malicious attackers attempt to launch adversarial attacks at ASV systems. In the midst of the arms race between attack and defense in ASV, how to effectively improve the robustness of ASV against adversarial attacks remains an open question. We note that the self-supervised learning models possess the ability to mitigate superficial perturbations in the input after pretraining. Hence, with the goal of effective defense in ASV against adversarial attacks, we propose a standard and attack-agnostic method based on cascaded self-supervised learning models to purify the adversarial perturbations. Experimental results demonstrate that the proposed method achieves effective defense performance and can successfully counter adversarial attacks in scenarios where attackers may either be aware or unaware of the self-supervised learning models.

eess.AS↗

arXiv2020

Defense for Black-box Attacks on Anti-spoofing Models by Self-Supervised Learning

High-performance anti-spoofing models for automatic speaker verification (ASV), have been widely used to protect ASV by identifying and filtering spoofing audio that is deliberately generated by text-to-speech, voice conversion, audio replay, etc. However, it has been shown that high-performance anti-spoofing models are vulnerable to adversarial attacks. Adversarial attacks, that are indistinguishable from original data but result in the incorrect predictions, are dangerous for anti-spoofing models and not in dispute we should detect them at any cost. To explore this issue, we proposed to employ Mockingjay, a self-supervised learning based model, to protect anti-spoofing models against adversarial attacks in the black-box scenario. Self-supervised learning models are effective in improving downstream task performance like phone classification or ASR. However, their effect in defense for adversarial attacks has not been explored yet. In this work, we explore the robustness of self-supervised learned high-level representations by using them in the defense against adversarial attacks. A layerwise noise to signal ratio (LNSR) is proposed to quantize and measure the effectiveness of deep models in countering adversarial noise. Experimental results on the ASVspoof 2019 dataset demonstrate that high-level representations extracted by Mockingjay can prevent the transferability of adversarial examples, and successfully counter black-box attacks.

eess.AS↗

arXiv2020

Phonon heat transport in cavity-mediated optomechanical nanoresonators

The understanding of heat transport in nonequilibrium thermodynamics is an important research frontier, which is crucial for implementing novel thermodynamic devices, such as heat engines and refrigerators. The convection, conduction, and radiation are the well-known basic ways to transfer thermal energy. Here we demonstrate a new mechanism of phonon heat transport between two spatially separated nanomechanical resonators coupled by the cavity-enhanced long-range interactions. The single trajectory for thermalization and non-equilibrium dynamics is monitored in real-time. We find that, in the strong coupling regime, instant heat flux counterintuitively oscillates back and forth in nonequilibrium steady states, which occurs spontaneously above the critical point during the thermal energy transfer process. The universal bound on the precision of nonequilibrium steady-state heat flux, i.e. the thermodynamic uncertainty relation, is verified in such a temperature gradient driven far-off equilibrium system. Our results reveal a previously unobserved phenomenon for heat transfer with mechanical oscillators, and provide a playground for testing fundamental theories in non-equilibrium thermodynamics.

physics.optics↗

arXiv2020

Self-organized synchronization of phonon lasers

Self-organized synchronization is a ubiquitous collective phenomenon, in which each unit adjusts their rhythms to achieve synchrony through mutual interactions. The optomechanical systems, due to their inherently engineerable nonlinearities, provide an ideal platform to study self-organized synchronization. Here, we demonstrate the self-organized synchronization of phonon lasers in a two-membrane-in-the-middle optomechanical system. The probe of individual membrane enables to monitor the real-time transient dynamics of synchronization, which reveal that the system enters into the synchronization regime via torus birth bifurcation line. The phase-locking phenomenon and the transition between in-phase and anti-phase regimes are directly observed. Moreover, such a system greatly facilitate the controllable synchronous states, and consequently a phononic memory is realized by tuning the system parameters. This result is an important step towards the future studies of many-body collective behaviors in multiresonator optomechanics with long distances, and might find potential applications in quantum information processing and complex networks.

physics.optics↗

arXiv2020

Defense against adversarial attacks on spoofing countermeasures of ASV

Various forefront countermeasure methods for automatic speaker verification (ASV) with considerable performance in anti-spoofing are proposed in the ASVspoof 2019 challenge. However, previous work has shown that countermeasure models are vulnerable to adversarial examples indistinguishable from natural data. A good countermeasure model should not only be robust against spoofing audio, including synthetic, converted, and replayed audios; but counteract deliberately generated examples by malicious adversaries. In this work, we introduce a passive defense method, spatial smoothing, and a proactive defense method, adversarial training, to mitigate the vulnerability of ASV spoofing countermeasure models against adversarial examples. This paper is among the first to use defense methods to improve the robustness of ASV spoofing countermeasure models under adversarial attacks. The experimental results show that these two defense methods positively help spoofing countermeasure models counter adversarial examples.

eess.AS↗

arXiv2019

Cooper pair polaritons in cold fermionic atoms within a cavity

We formulate a Bardeen-Cooper-Schriffer (BCS) theory of quasiparticles in a degenerate Fermi gas strongly coupled to photons in a optical cavity. The elementary photonic excitations of the system are cavity polaritons, which consist of a cavity photon and an excitation of an atom within the Fermi sea. The excitation of the atom out of the Fermi sea leaves behind a hole, which together results in a loosely bound Cooper pair, allowing for the system to be written by a BCS wavefunction. As the density of the excitations is increased, the excited atom and hole become more strongly bound, crossing over into the molecular regime. This thus realizes an alternative BCS to BEC crossover scenario, where the participating species are quasiparticle excitations in a Fermi sea consisting of excited atoms and holes.

cond-mat.quant-gas↗

arXiv2019

Adversarial Attacks on Spoofing Countermeasures of automatic speaker verification

High-performance spoofing countermeasure systems for automatic speaker verification (ASV) have been proposed in the ASVspoof 2019 challenge. However, the robustness of such systems under adversarial attacks has not been studied yet. In this paper, we investigate the vulnerability of spoofing countermeasures for ASV under both white-box and black-box adversarial attacks with the fast gradient sign method (FGSM) and the projected gradient descent (PGD) method. We implement high-performing countermeasure models in the ASVspoof 2019 challenge and conduct adversarial attacks on them. We compare performance of black-box attacks across spoofing countermeasure models with different network architectures and different amount of model parameters. The experimental results show that all implemented countermeasure models are vulnerable to FGSM and PGD attacks under the scenario of white-box attack. The more dangerous black-box attacks also prove to be effective by the experimental results.

eess.AS↗

arXiv2019

Twin-beam-enhanced displacement measurement of a membrane in a cavity

Ultrasensitive measurement of a small displacement is an essential goal in various applications of science and technology, ranging from large-scale laser interferometric gravitational wave detectors to micro-electro-mechanical-systems-based force microscopy. The least measurable displacement is ultimately limited by the quantum nature of light in a classical optical sensor. Here we use the bright quantum correlated light, i.e., twin beams, generated by a coherent atomic medium to surpass the shot-noise limit (SNL) of the displacement measurement of a membrane in an optical cavity. The sensitivity of 200 $am/\sqrt {Hz}$ is achieved, which is more than two orders of magnitude better than a standard Michelson interferometer. An improvement of 3 $dB$ in the signal-to-noise ratio (SNR) beyond the SNL is realized at an equivalent optical power, by using quantum correlated light with noise squeezed 7 $dB$ below the vacuum level. Moreover, the frequency correlation of twin beams is directly measured by using optical cavities, and this relation is utilized to reduce the excess classical noise. Additionally, the displacement measurement sensitivity is further substantially enhanced by the cavity mediated dispersion and the SNR is increased by one order of magnitude compared to the free space case. These results provide a novel strategy for the world of precision measurement as well as to control cavity optomechanical systems with non-classical light.

physics.optics↗

arXiv2018

A controllable two-membrane-in-the-middle cavity optomechanical system

We report an optomechanical system with two dielectric membranes inside a Fabry-Perot cavity. The cavity resonant frequencies are measured in such a two-membrane-in-the-middle system, which show an interesting band-structure-like diagram. This system exhibits great controllability on the parameters of the system. The positions and angles of each membrane can be manipulated on demand by placing two membranes inside the cavity separately. The eigenfrequencies of the vibrational modes of the membranes can also be tuned individually with piezoelectricity. This scheme could be straightforwardly extended to multiple-membrane-in-the-middle systems, where more than two membranes are involved. Such a well controllable multiple membrane optomechanical system provides a promising platform for studying nonlinear and quantum dynamical phenomena in multimode optomechanics with distinct mechanical oscillators.

physics.optics↗

arXiv2018

Shortcuts to adiabaticity in Fermi gases

Shortcuts to adiabaticity (STA) provide an alternative to adiabatic protocols to guide the dynamics of the system of interest without the requirement of slow driving. We report the controlled speedup via STA of the nonadiabatic dynamics of a Fermi gas, both in the non-interacting and strongly coupled, unitary regimes. Friction-free superadiabatic expansion strokes, with no residual excitations in the final state, are demonstrated in the unitary regime by engineering the modulation of the frequencies and aspect ratio of the harmonic trap. STA are also analyzed and implemented in the high-temperature regime, where the shear viscosity plays a pivotal role and the Fermi gas is described by viscous hydrodynamics.

quant-ph↗

arXiv2018

Friction-free quantum machines

The operation of a quantum heat engine in finite time generally faces a trade-off between efficiency and power. Using shortcuts to adiabaticity (STA), this trade off can be avoided to engineer thermal machines that operate at maximum efficiency and tunable output power. We demonstrate the use of STA to engineer a scalable superadiabatic quantum Otto cycle and report recent experimental progress to tailor quantum friction in finite-time quantum thermodynamics. In the presence of quantum friction, it is also shown that the use of a many-particle working medium can boost the performance of the quantum machines with respect to an ensemble of single-particle thermal machines.

quant-ph↗