scholarly journals Alteration Of The Frequency Profile Of Voice Signals

2020 ◽  
Author(s):  
Essaid Bouktache ◽  
Chandra R. Sekhar ◽  
Omer Farook
Keyword(s):  
Frequency Profile

Productive Vocabulary Knowledge of ESL Learners

2018 ◽  
Vol 1 (1) ◽  
pp. 32-41 ◽  
Author(s):  
Abdulmalik Usman ◽  
Dahiru Musa Abdullahi
Keyword(s):  
Teaching And Learning ◽  
English Language ◽  
Vocabulary Knowledge ◽  
Writing Quality ◽  
Lexical Frequency ◽  
Frequency Profile ◽  
Esl Learners ◽  
The Relationship

The paper seeks to investigate the level of productive knowledge of ESL learners, the writing quality and the relationship between the vocabulary knowledge and the writing quality. 150 final year students of English language in a university in Nigeria were randomly selected as respondents. The respondents were asked to write an essay of 300 words within one hour. The essays were typed into Vocab Profiler of Cobb (2002) and analyzed the Lexical Frequency Profile of the respondents. The essays were also assessed by independent examiners using a standard rubric. The findings reveal that the level of productive vocabulary knowledge of the respondents is limited. The writing quality of the majority of the respondent is fair and there is a significant correlation between vocabulary and the witting quality of the subjects. The researchers posit that productive vocabulary is the predictor of writing quality and recommend various techniques through which teaching and learning of vocabulary can be improved.

Automatic Recognition of the Lighting Whistler waves from the Wave Data of SCM Boarded on ZH-1 satellite

2021 ◽  
Author(s):  
Jing Yuan ◽  
Zijie Wang ◽  
Dehe Yang ◽  
Qiao Wang ◽  
Zeren Zima ◽  
...  
Keyword(s):  
Short Term Memory ◽  
Satellite Observation ◽  
Original Data ◽  
Electromagnetic Environment ◽  
Mel Frequency Cepstral Coefficients ◽  
Frequency Profile ◽  
Time Frequency ◽  
Wave Data ◽  
Audio Clip ◽  
Long Short Term Memory

<p>Lightning whistlers, found frequently in electromagnetic satellite observation, are the important tool to study electromagnetic environment of the earth space. With the increasing data from electromagnetic satellites, a considerable amount of time and human efforts are needed to detect lightning whistlers from these tremendous data. In recent years, algorithms for lightning whistlers automatic detection have been conducted. However, these methods can only work in the time-frequency profile (image) of the electromagnetic satellites data with two major limitations: vast storage memory for the time-frequency profile (image) and expensive computation for employing the methods to detect automatically the whistler from the time-frequency profile. These limitations hinder the methods work efficiently on ZH-1 satellite. To overcome the limitations and realize the real-time whistler detection automatically on board satellite, we propose a novel algorithm for detecting lightning whistler from the original observed data without transforming it to the time-frequency profile (image).</p><p>The motivation is that the frequency of lightning whistler is in the audio frequency range. It encourages us to utilize the speech recognition techniques to recognize the whistler in the original data \of SCM VLF Boarded on ZH-1. Firstly, we averagely move a 0.16 seconds window on the original data to obtain the patch data as the audio clip. Secondly, we extract the Mel-frequency cepstral coefficients (MFCCs) of the patch data as a type of cepstral representation of the audio clip. Thirdly, the MFCCs are input to the Long Short-Term Memory (LSTM) recurrent neutral networks to classification. To evaluate the proposed method, we construct the dataset composed of 10000 segments of SCM wave data observed from ZH-1 satellite(5000 segments which involving whistler and 5000 segments without any whistler). The proposed method can achieve 84% accuracy, 87% in recall, 85.6% in F1score.Furthermore, it can save more than 126.7MB and 0.82 seconds compared to the method employing the YOLOv3 neutral network for detecting whistler on each time-frequency profile.</p><p> </p><p>Key words: ZH-1 satellite, SCM,lightning whistler, MFCC, LSTM</p>

scholarly journals Vocabulary size and use: Lexical richness in L2 written production

2020 ◽  
Author(s):  
B Laufer ◽  
Paul Nation
Keyword(s):  
High Frequency ◽  
Close Correspondence ◽  
Vocabulary Size ◽  
Reliable Measure ◽  
Lexical Frequency ◽  
Frequency Profile ◽  
Oxford University ◽  
Lexical Richness ◽  
Vocabulary Growth ◽  
General Service

This article shows that if there is some control over genre then there will be a close correspondence between the vocabulary size of intermediate learners as reflected in their writing and a more direct measure of vocabulary size The study proposes a new measure of lexical richness, the Lexical Frequency Profile, which looks at the proportion of high frequency general service and academic words in learners' writing The study shows that it is possible to obtain a reliable measure of lexical richness which is stable across two pieces of writing by the same learners It also discriminates between learners of different proficiency levels For learners of English as a second language, the Lexical Frequency Profile is seen as being a measure of how vocabulary size is reflected in use In this study, it was found that the Lexical Frequency Profile correlates well with an independent measure of vocabulary size This reliable and valid measure of lexical richness in writing will be useful for determining the factors that affect judgements of quality in writing and will be useful for examining how vocabulary growth is related to vocabulary use. © 1995 Oxford University Press.

scholarly journals Vocabulary size and use: Lexical richness in L2 written production

2020 ◽  
Author(s):  
B Laufer ◽  
Paul Nation
Keyword(s):  
High Frequency ◽  
Close Correspondence ◽  
Vocabulary Size ◽  
Reliable Measure ◽  
Lexical Frequency ◽  
Frequency Profile ◽  
Oxford University ◽  
Lexical Richness ◽  
Vocabulary Growth ◽  
General Service

This article shows that if there is some control over genre then there will be a close correspondence between the vocabulary size of intermediate learners as reflected in their writing and a more direct measure of vocabulary size The study proposes a new measure of lexical richness, the Lexical Frequency Profile, which looks at the proportion of high frequency general service and academic words in learners' writing The study shows that it is possible to obtain a reliable measure of lexical richness which is stable across two pieces of writing by the same learners It also discriminates between learners of different proficiency levels For learners of English as a second language, the Lexical Frequency Profile is seen as being a measure of how vocabulary size is reflected in use In this study, it was found that the Lexical Frequency Profile correlates well with an independent measure of vocabulary size This reliable and valid measure of lexical richness in writing will be useful for determining the factors that affect judgements of quality in writing and will be useful for examining how vocabulary growth is related to vocabulary use. © 1995 Oxford University Press.

scholarly journals High-frequency profile in adolescents and its relationship with the use of personal stereo devices

2016 ◽  
Vol 92 (2) ◽  
pp. 206-211 ◽  
Author(s):  
Renata Almeida Araújo Silvestre ◽  
Ângela Ribas ◽  
Rogério Hammerschmidt ◽  
Adriana Bender Moreira de Lacerda
Keyword(s):  
High Frequency ◽  
Frequency Profile

Frequency profile generated from left atrial activation in patients with paroxysmal atrial fibrillation

2007 ◽  
Vol 40 (4) ◽  
pp. S48
Author(s):  
Keisuke Kawachi ◽  
Takeshi Tsutsumi ◽  
Daisuke Wakatsuki ◽  
Kei Ota ◽  
Nami Kubota ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Paroxysmal Atrial Fibrillation ◽  
Left Atrial ◽  
Frequency Profile ◽  
Atrial Activation
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