A data-driven speech intelligibility assessment method using sum-sorted spectrogram feature

2016 ◽  
Author(s):  
Jia Xupeng ◽  
Li Dongmei
Keyword(s):  
Speech Intelligibility ◽  
Assessment Method ◽  
Data Driven ◽  
Spectrogram Feature

The route problem of multimodal transportation with timetable: stochastic multi-objective optimization model and data-driven simheuristic approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yong Peng ◽  
Yi Juan Luo ◽  
Pei Jiang ◽  
Peng Cheng Yong
Keyword(s):  
Risk Assessment ◽  
Optimization Model ◽  
Assessment Method ◽  
Data Driven ◽  
Nsga Ii ◽  
Multimodal Transportation ◽  
Retention Strategy ◽  
Content Type ◽  
Risk Assessment Method ◽  
Mc Simulation

PurposeDistribution of long-haul goods could be managed via multimodal transportation networks where decision-maker has to consider these factors including the uncertainty of transportation time and cost, the timetable limitation of selected modes and the storage cost incurred in advance or delay arriving of the goods. Considering the above factors comprehensively, this paper establishes a multimodal multi-objective route optimization model which aims to minimize total transportation duration and cost. This study could be used as a reference for decision-maker to transportation plans.Design/methodology/approachMonte Carlo (MC) simulation is introduced to deal with transportation uncertainty and the NSGA-II algorithm with an external archival elite retention strategy is designed. An efficient transformation method based on data-drive to overcome the high time-consuming problem brought by MC simulation. Other contribution of this study is developed a scheme risk assessment method for the non-absolutely optimal Pareto frontier solution set obtained by the NSGA-II algorithm.FindingsNumerical examples verify the effectiveness of the proposed algorithm as it is able to find a high-quality solution and the risk assessment method proposed in this paper can provide support for the route decision.Originality/valueThe impact of timetable on transportation duration is analyzed and making a detailed description in the mathematical model. The uncertain transportation duration and cost are represented by random number that obeys a certain distribution and designed NSGA-II with MC simulation to solve the proposed problem. The data-driven strategy is adopted to reduce the computational time caused by the combination of evolutionary algorithm and MC simulation. The elite retention strategy with external archiving is created to improve the quality of solutions. A risk assessment approach is proposed for the solution scheme and in the numerical simulation experiment.

scholarly journals Robust Data-Driven Auditory Profiling Towards Precision Audiology

2020 ◽  
Vol 24 ◽  
pp. 233121652097353
Author(s):  
Raul Sanchez-Lopez ◽  
Michal Fereczkowski ◽  
Tobias Neher ◽  
Sébastien Santurette ◽  
Torsten Dau
Keyword(s):  
Hearing Loss ◽  
Speech Intelligibility ◽  
Dimensional Space ◽  
Hearing Threshold ◽  
Low Frequency ◽  
Pure Tone Audiometry ◽  
Data Driven ◽  
Type I ◽  
Data Set ◽  
Distortion Type

The sources and consequences of a sensorineural hearing loss are diverse. While several approaches have aimed at disentangling the physiological and perceptual consequences of different etiologies, hearing deficit characterization and rehabilitation have been dominated by the results from pure-tone audiometry. Here, we present a novel approach based on data-driven profiling of perceptual auditory deficits that attempts to represent auditory phenomena that are usually hidden by, or entangled with, audibility loss. We hypothesize that the hearing deficits of a given listener, both at hearing threshold and at suprathreshold sound levels, result from two independent types of “auditory distortions.” In this two-dimensional space, four distinct “auditory profiles” can be identified. To test this hypothesis, we gathered a data set consisting of a heterogeneous group of listeners that were evaluated using measures of speech intelligibility, loudness perception, binaural processing abilities, and spectrotemporal resolution. The subsequent analysis revealed that distortion type-I was associated with elevated hearing thresholds at high frequencies and reduced temporal masking release and was significantly correlated with elevated speech reception thresholds in noise. Distortion type-II was associated with low-frequency hearing loss and abnormally steep loudness functions. The auditory profiles represent four robust subpopulations of hearing-impaired listeners that exhibit different degrees of perceptual distortions. The four auditory profiles may provide a valuable basis for improved hearing rehabilitation, for example, through profile-based hearing-aid fitting.

The Multi-Attributes Assessment Method of Control Performance Based on Data Driven

2014 ◽  
Vol 945-949 ◽  
pp. 2655-2660
Author(s):  
Liang Cai Qi ◽  
Hai Zhi Kong ◽  
Jian Wen Qiu ◽  
Yu Qiu Liu ◽  
Xiao Guang Du
Keyword(s):  
Decision Making ◽  
Case Studies ◽  
Assessment Method ◽  
Data Driven ◽  
Control Performance ◽  
Performance Indexes ◽  
Multi Attribute Decision Making

The performance of a controller is usually characterized by several attribute indexes. In this context, this paper applies multi-attribute decision-making techniques to the assessment of control performance, which takes into account both stochastic and deterministic performance indexes. Case studies demonstrate the validity of the proposed method.

scholarly journals Data-Driven Evaluation of Residential HVAC System Efficiency Using Energy and Environmental Data

Energies ◽  
2019 ◽  
Vol 12 (1) ◽  
pp. 188 ◽  
Author(s):  
Huyen Do ◽  
Kristen S. Cetin
Keyword(s):  
Assessment Tool ◽  
Demand Curve ◽  
Residential Buildings ◽  
Residential Building ◽  
Assessment Method ◽  
Electricity Demand ◽  
Environmental Data ◽  
Data Driven ◽  
Hvac System ◽  
Actual Performance

In the U.S., the heating, ventilation, and air conditioning (HVAC) system is generally the largest electricity-consuming end-use in a residential building. However, homeowners are less likely to have their HVAC system serviced regularly, thus inefficiencies in operation are also more likely to occur. To address this challenge, this research works towards a non-intrusive data-driven assessment method using building assessors’ data, HVAC electricity demand data, and outdoor environmental data. Building assessors’ data is first used to estimate the HVAC system size, then estimate the electricity demand curve of the HVAC system. A comparison of the proposed electricity demand curve development method demonstrates strong agreement with physics-based HVAC model results. An HVAC efficiency rating is then proposed, which compares the model-predicted and actual performance data to define whether an HVAC system is operating as expected. As a case study, detailed data for 39 occupied, conditioned residential buildings in Austin, Texas, was used demonstrating the identification of the presence of potential HVAC inefficiencies. The results prove beneficial for utilities to help target residential HVAC systems in need of service or energy efficiency upgrades, as well as for homeowners as a continuous assessment tool for HVAC performance.

scholarly journals Robust data-driven auditory profiling towards precision audiology

2020 ◽  
Author(s):  
Raul Sanchez-Lopez ◽  
Michal Fereczkowski ◽  
Tobias Neher ◽  
Sébastien Santurette ◽  
Torsten Dau
Keyword(s):  
Speech Intelligibility ◽  
Hearing Aid ◽  
Hearing Threshold ◽  
Data Driven ◽  
Hearing Aid Fitting ◽  
Binaural Processing ◽  
Sound Levels ◽  
Processing Abilities ◽  
Definition Of ◽  
The Individual

Data-driven profiling allows uncovering complex hidden structures in a dataset and has been used as a diagnostic tool in various fields of work. In audiology, the clinical characterization of hearing deficits for hearing-aid fitting is typically based on the pure-tone audiogram only. Implicitly, this relies on the assumption that the audiogram can predict a listener's supra-threshold hearing abilities. Sanchez-Lopez et al. [Trends in hearing vol. 22 (2018)] hypothesized that the hearing deficits of a given listener, both at hearing threshold and at supra-threshold sound levels, result from two independent types of "auditory distortions". The authors performed a data-driven analysis of two large datasets with results from numerous tests, which led to the identification of four distinct "auditory profiles". However, the definition of the two types of distortion was challenged by differences between the two datasets in terms of the selected tests and type of listeners included in the datasets. Here, a new dataset was generated with the aim of overcoming those limitations. A heterogeneous group of listeners (N = 75) was tested using measures of speech intelligibility, loudness perception, binaural processing abilities and spectro-temporal resolution. The subsequent data analysis allowed refining the auditory profiles proposed by Sanchez-Lopez et al. (2018). Besides, a robust iterative data-driven method is proposed here to reduce the influence of the individual data in the definition of the auditory profiles. The updated auditory profiles may provide a useful basis for improved hearing rehabilitation, e.g. through profile-based hearing-aid fitting.

Sign in / Sign up

Export Citation Format

Share Document