Timbre Vocálico en Hablantes De Español Como Segunda Lengua

Mella, Magaly Ruiz; Soto-Barba, Jaime

doi:10.7764/onomazein.11.04

Onomázein 2005

DOI: 10.7764/onomazein.11.04

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Timbre Vocálico en Hablantes De Español Como Segunda Lengua

Magaly Ruiz Mella

Jaime Soto-Barba

Abstract: En este trabajo, se presentan los resultados de un estudio en el que se comparan las manifestaciones acústicas del F1 y el F2 de las vocales españolas pronunciadas por seis hablantes de esta lengua como L2 con los formantes vocálicos de estos mismos sonidos articulados por un hablante representativo del español de Concepción (Chile), y también con el F1 y el F2 de las vocales sintetizadas del español descritas por Delattre (1962).

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“…'. These situations are identified through the analysis of the formants, which correspond to the frequency of the largest magnitudes for each time instant of the communication [11][12][13]. Speech phonemes are described by the first and second formants, which are obtained by analyzing the spectrogram of the audio file containing the communication records.…”

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confidence: 99%

“…Formants are obtained by means of analysis in the frequency domain through a spectrogram that represents the intensity of the signal for each frequency within its bandwidth and for each discrete time instant of the recorded signal. In Spanish, the phonemes are determined by the frequency and magnitude of the first two formants, as can be seen in [12,28]. Thus, there are the so-called letters of formants (LoF), which allow us to identify the use of vowels.…”

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See 1 more Smart Citation

Uncertainty Detection in Supervisor–Operator Audio Records of Real Electrical Network Operations

Acevedo,

Garcia,

Ramirez

et al. 2023

Electronics

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The quality of verbal communication, understood as the absence of uncertainty in the message transmitted, is a key factor in mission-critical processes. Several processes are handled by direct voice communication between these endpoints and any miscommunication could have an impact in success of the task. For that reason, the quality control of verbal communication is required to ensure that the instructions issued are effectively understood and adequately executed. In this context, it is expected that instructions from the command center are issued once, and that the acknowledgment from the field are minimal. In the present work, the communication between an electrical company control center and factory workers in the field was chosen for analysis. We developed two complementary approaches by using machine learning and deep learning algorithms to assess, in an automatic way, the quality of information transmission in the voice communications. Preliminary results demonstrate that the automatic uncertainty detection is feasible, despite the small number of samples available at the present time. To support further studies, a repository was created in GitHub with the spectrogram and the tokenized words of all audios.

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confidence: 99%

mentioning

confidence: 99%

Uncertainty Detection in Supervisor–Operator Audio Records of Real Electrical Network Operations

Acevedo,

Garcia,

Ramirez

et al. 2023

Electronics

View full text Add to dashboard Cite

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Stress-Induced Acoustic Variation in L2 and L1 Spanish Vowels

2018

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Aim: We assessed the effect of lexical stress on the duration and quality of Spanish word-final vowels /a, e, o/ produced by American English late intermediate learners of L2 Spanish, as compared to those of native L1 Argentine Spanish speakers. Methods: Participants read 54 real words ending in /a, e, o/, with either final or penultimate lexical stress, embedded in a text and a word list. We measured vowel duration and both F1 and F2 frequencies at 3 temporal points. Results: stressed vowels were longer than unstressed vowels, in Spanish L1 and L2. L1 and L2 Spanish stressed /a/ and /e/ had higher F1 values than their unstressed counterparts. Only the L2 speakers showed evidence of rising offglides for /e/ and /o/. The L2 and L1 Spanish vowel space was compressed in the absence of stress. Conclusion: Lexical stress affected the vowel quality of L1 and L2 Spanish vowels. We provide an up-to-date account of the formant trajectories of Argentine River Plate Spanish word-final /a, e, o/ and offer experimental support to the claim that stress affects the quality of Spanish vowels in word-final contexts.

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Reconocimiento de Patrones Vocálicos mediante la implementación de una red Neuronal Artificial Utilizando Sistemas Embebidos

2016

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ResumenEn este trabajo se presentan los resultados del diseño y desarrollo de una red neuronal de tipo feed-forward en un sistema embebido, para identificar patrones asociados con la pronunciación de fonemas vocálicos del idioma español. Para el entrenamiento de la red fueron utilizados los coeficientes cepstrales de las frecuencias de Mel (MFCC), extraídos a partir de señales de audio provenientes de la pronunciación de las vocales abiertas (/a/, /e/ y /o/). La captura de nuevas muestras se realizó a través de un computador y un sistema embebido para la evaluación, comprobación y comparación del desempeño de la red neuronal. Se obtuvo un porcentaje de identificación correcta por encima del 98%. Esto indica que el error en la separación de clases fue inferior al 2% en la red neuronal al momento de evaluar patrones asociados a alguna de las tres vocales. Basado en los resultados obtenidos se concluye que la implementación de algoritmos de inteligencia artificial para tareas de clasificación en sistemas embebidos es factible, y presenta resultados similares a los que tendría el mismo sistema operando con los recursos de un computador. Palabras clave: red neuronal; señales de audio; sistema embebido; coeficientes cepstrales; reconocimiento del habla Recognition of Vowel Patterns by Implementing an Artificial Neural Network in an Embedded System AbstractIn this work the results of the design and development of a neural network type feed-forward in an embedded system, to identify patterns associated with the pronunciation of vowels of Spanish language are presented. For the training of the network Mel frequencies cepstrals coefficients extracted from audio signals related to the pronunciation of the open vowels (/ a /, /e/ and /o/) were used. The capture of new samples was performed by using a computer and an embedded system to evaluate, test and compare the performance of the neural network. A percentage of correct identification above 98% was obtained indicating that the error in the class separation was less than 2% for patterns obtained from any of the three vowels. Based on the results it is concluded that implementation of artificial intelligence algorithms for classification tasks in embedded systems is feasible, and presents similar results to those that would have the same system working with the resources of a computer.

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Timbre Vocálico en Hablantes De Español Como Segunda Lengua

Cited by 3 publications

References 4 publications

Uncertainty Detection in Supervisor–Operator Audio Records of Real Electrical Network Operations

Uncertainty Detection in Supervisor–Operator Audio Records of Real Electrical Network Operations

Stress-Induced Acoustic Variation in L2 and L1 Spanish Vowels

Reconocimiento de Patrones Vocálicos mediante la implementación de una red Neuronal Artificial Utilizando Sistemas Embebidos

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