Word learning in the lab is hard! Data from 14-month-old monolingual and bilingual infants

Infants can learn words in their daily interactions early in life, and many studies have demonstrated that they can also learn words from brief in-lab exposures. While most studies have included monolingual infants, less is known about bilingual infants’ word learning and the role that language familiarity plays in this ability. In this study we examined word learning in a large sample (up to N = 155) of bilingual and monolingual 14-month-olds using a preferential looking paradigm. To support word learning, novel words were presented within sentence frames in one language (single-language condition) or two languages (dual-language condition). We predicted that infants would exhibit greater word–object learning when they were more familiar with the language of the sentence frame. Using both traditional (t-tests) and updated (linear mixed-effects models) analyses, we found no evidence for successful word learning, nor an effect of familiarity. Our results suggest that word learning in experimental settings can be challenging for 14-month-olds, even when sentence frames are provided. We discuss these results in relation to prior work and suggest how open science practices can contribute to more reliable findings about early word learning.

Rapid neural encoding of the contrast between native and nonnative speech in the alpha band

More than half of the world's population is multilingual, yet it is not known how the human brain encodes the perception of native vs. nonnative speech. To find out, we asked German native speakers to detect the onset of native and nonnative (English and Turkish) vowels in a roving standard stimulation. Using EEG, we show that nonnativeness is robustly registered by an increase in phase coherence in the alpha band (8-12 Hz), beginning as early as ~100 ms after stimulus onset and lasting more than 200 ms. The alpha band effect is speech-specific, successfully predicts the response speed advantage of nonnative speech, and grants ~90% decoding accuracy in distinguishing native vs. nonnative speech irrespective of language familiarity. We propose alpha phase coherence as a candidate neural channel for the online resolution of the native-nonnative contrast in the adult brain.

A powerful comparison of deep learning frameworks for Arabic sentiment analysis

Deep learning (DL) is a machine learning (ML) subdomain that involves algorithms taken from the brain function named artificial neural networks (ANNs). Recently, DL approaches have gained major accomplishments across various Arabic natural language processing (ANLP) tasks, especially in the domain of Arabic sentiment analysis (ASA). For working on Arabic SA, researchers can use various DL libraries in their projects, but without justifying their choice or they choose a group of libraries relying on their particular programming language familiarity. We are basing in this work on Java and Python programming languages because they have a large set of deep learning libraries that are very useful in the ASA domain. This paper focuses on a comparative analysis of different valuable Python and Java libraries to conclude the most relevant and robust DL libraries for ASA. Throw this comparative analysis, and we find that: TensorFlow, Theano, and Keras Python frameworks are very popular and very used in this research domain.

Talker Processing in Mandarin-Speaking Congenital Amusics

Purpose The ability to recognize individuals from their vocalizations is an important trait of human beings. In the current study, we aimed to examine how congenital amusia, an inborn pitch-processing disorder, affects discrimination and identification of talkers' voices. Method Twenty Mandarin-speaking amusics and 20 controls were tested on talker discrimination and identification in four types of contexts that varied in the degree of language familiarity: Mandarin real words, Mandarin pseudowords, Arabic words, and reversed Mandarin speech. Results The language familiarity effect was more evident in the talker identification task than the discrimination task for both participant groups, and talker identification accuracy decreased as native phonological representations were removed from the stimuli. Importantly, amusics demonstrated degraded performance in both native speech conditions that contained phonological/linguistic information to facilitate talker identification and nonnative conditions where talker voice processing primarily relied on phonetics cues, including pitch. Moreover, the performance in talker processing can be predicted by the participants' musical ability and phonological memory capacity. Conclusions The results provided a first set of behavioral evidence that individuals with amusia are impaired in the ability of human voice identification. Meanwhile, it is found that amusia is not only a pitch disorder but is likely to affect the phonological processing of speech, in terms of using phonological information in native speech to analyze a talker's identity. The above findings expanded the understanding of the nature and scope of congenital amusia. Supplemental Material https://doi.org/10.23641/asha.12170379