In three experiments, we examined priming effects where primes were formed by transposing the first and last phoneme of tri‐phonemic target words (e.g., /byt/ as a prime for /tyb/). Auditory lexical decisions were found not to be sensitive to this transposed‐phoneme priming manipulation in long‐term priming (Experiment 1), with primes and targets presented in two separated blocks of stimuli and with unrelated primes used as control condition (/mul/‐/tyb/), while a long‐term repetition priming effect was observed (/tyb/‐/tyb/). However, a (...) clear transposed‐phoneme priming effect was found in two short‐term priming experiments (Experiments 2 and 3), with primes and targets presented in close temporal succession. The transposed‐phoneme priming effect was found when unrelated prime‐target pairs (/mul/‐/tyb/) were used as control and more important when prime‐target pairs sharing the medial vowel (/pys/‐/tyb/) served as control condition, thus indicating that the effect is not due to vocalic overlap. Finally, in Experiment 3, a transposed‐phoneme priming effect was found when primes sharing the medial vowel plus one consonant in an incorrect position with the targets (/byl/‐/tyb/) served as control condition, and this condition did not differ significantly from the vowel‐only condition. Altogether, these results provide further evidence for a role for position‐independent phonemes in spoken word recognition, such that a phoneme at a given position in a word also provides evidence for the presence of words that contain that phoneme at a different position. (shrink)

Norris, McQueen & Cutler present a detailed account of the decision stage of the phoneme monitoring task. However, we question whether this contributes to our understanding of the speech recognition process itself, and we fail to see why phonotactic knowledge is playing a role in phoneme recognition.

"ACT Administrative Appeals Tribunal Decisions." Ethos: Official Publication of the Law Society of the Australian Capital Territory, (200), pp. 42.

Top-down feedback does not benefit speech recognition; on the contrary, it can hinder it. No experimental data imply that feedback loops are required for speech recognition. Feedback is accordingly unnecessary and spoken word recognition is modular. To defend this thesis, we analyse lexical involvement in phonemic decision making. TRACE (McClelland & Elman 1986), a model with feedback from the lexicon to prelexical processes, is unable to account for all the available data on phonemic decision making. The modular Race (...) model (Cutler & Norris 1979) is likewise challenged by some recent results, however. We therefore present a new modular model of phonemic decision making, the Merge model. In Merge, information flows from prelexical processes to the lexicon without feedback. Because phonemic decisions are based on the merging of prelexical and lexical information, Merge correctly predicts lexical involvement in phonemic decisions in both words and nonwords. Computer simulations show how Merge is able to account for the data through a process of competition between lexical hypotheses. We discuss the issue of feedback in other areas of language processing and conclude that modular models are particularly well suited to the problems and constraints of speech recognition. Key Words: computational modeling; feedback; lexical processing; modularity; phonemic decisions; reading; speech recognition; word recognition. (shrink)

The model of phoneme monitoring proposed by Norris et al. is implausible when implemented in a localist connectionist network. Lexical representations mysteriously inform phoneme decision nodes as to the presence or absence of a target phoneme.

Our commentary outlines a number of arguments questioning an autonomous model of word recognition without feedback. Arguments are presented against the need for a phonemic decision stage and in support of a featural level in a model including feedback.

We applaud Norris et al.'s critical review of the literature on lexical effects in phoneme decision making, and we sympathize with their attempt to reconcile autonomous models of word recognition with current research. However, we suggest that adaptive resonance theory (ART) may provide a coherent account of the data while preserving limited inhibitory feedback among certain lexical and sublexical representations.

In this study, we examined whether the lexical competition process embraced by most models of spoken word recognition is sensitive to talker-specific information. We used a lexical decision task and a long lag priming experiment in which primes and targets sharing all phonemes except the last one were presented in two separate blocks of stimuli. In Experiment 1, the competitor prime block was presented only once to listeners, and no modulation of the competitor priming effect as a function of a (...) talker change between the primes and targets was observed. However, attenuation in the competitor priming effect in the case of a talker change between the primes and targets was observed in Experiment 2 in which the competitor prime block was presented five times to listeners. We discuss our findings in reference to hybrid models of spoken word recognition in which repetition of words with the same talker could be a key factor in the formation and access to talker-dependent representations. (shrink)

Visual word recognition is facilitated by the presence of orthographic neighbors that mismatch the target word by a single letter substitution. However, researchers typically do not consider where neighbors mismatch the target. In light of evidence that some letter positions are more informative than others, we investigate whether the influence of orthographic neighbors differs across letter positions. To do so, we quantify the number of enemies at each letter position (how many neighbors mismatch the target word at that position). Analyses (...) of reaction time data from a visual word naming task indicate that the influence of enemies differs across letter positions, with the negative impacts of enemies being most pronounced at letter positions where readers have low prior uncertainty about which letters they will encounter (i.e., positions with low entropy). To understand the computational mechanisms that give rise to such positional entropy effects, we introduce a new computational model, VOISeR (Visual Orthographic Input Serial Reader), which receives orthographic inputs in parallel and produces an over‐time sequence of phonemes as output. VOISeR produces a similar pattern of results as in the human data, suggesting that positional entropy effects may emerge even when letters are not sampled serially. Finally, we demonstrate that these effects also emerge in human subjects' data from a lexical decision task, illustrating the generalizability of positional entropy effects across visual word recognition paradigms. Taken together, such work suggests that research into orthographic neighbor effects in visual word recognition should also consider differences between letter positions. (shrink)

Children learning to read in two different orthographic systems are exposed to cross-linguistic interferences. We explored the effects of school and grade on phonological activation during a visual word recognition task. Elementary school children from Spain completed a lexical decision task in English. The task included real words and pseudohomophones following Spanish or English phonological rules. Using the mouse-tracking paradigm, we analyzed errors, reaction times, and computer mouse movements. Children in the bilingual school performed better than children in the monolingual (...) school. Children in higher grades performed better than children in lower grades. The interference effect of Spanish phonology was weak and became weaker in higher grades. Spanish children differentiate between first and second language grapheme-to-phoneme correspondences since early on in the educational process. In 6th grade, children from the bilingual school responded better to words and Spanish pseudohomophones, while children from the monolingual school were less distracted by the English pseudohomophones. Children in the bilingual school had stronger inhibition of Spanish phonology and stronger activation of English phonology. Instructional method plays an important role on the processing strategies Spanish children rely on when reading in English. School and grade influence the link between orthographic and phonological representations. (shrink)

Before the end of the first year of life, infants begin to lose the ability to perceive distinctions between sounds that are not phonemic in their native language. It is typically assumed that this developmental change reflects the construction of language-specific phoneme categories, but how these categories are learned largely remains a mystery. Peperkamp, Le Calvez, Nadal, and Dupoux (2006) present an algorithm that can discover phonemes using the distributions of allophones as well as the phonetic properties of the (...) allophones and their contexts. We show that a third type of information source, the occurrence of pairs of minimally differing word forms in speech heard by the infant, is also useful for learning phonemic categories and is in fact more reliable than purely distributional information in data containing a large number of allophones. In our model, learners build an approximation of the lexicon consisting of the high-frequency n-grams present in their speech input, allowing them to take advantage of top-down lexical information without needing to learn words. This may explain how infants have already begun to exhibit sensitivity to phonemic categories before they have a large receptive lexicon. (shrink)

Symbolic representation acquisition is the complex cognitive process consisting of learning to use a symbol to stand for something else. A variety of non-human animals can engage in symbolic representation learning. One particularly complex form of symbol representation is the associations between orthographic symbols and speech sounds, known as grapheme–phoneme correspondence. To date, there has been little evidence that animals can learn this form of symbolic representation. Here, we evaluated whether an Umbrella cockatoo (Cacatua alba) can learn letter-speech correspondence using (...) English words. The bird-participant was trained with phonics instruction and then tested on pairs of index cards while the experimenter spoke the word. The words were unknown to the bird and the experimenter was blinded to the correct card position. The cockatoo’s accuracy (M = 71%) was statistically significant. Further, we found a strong correlation between the bird’s word-identification success and the number of overlapping letters between words, where the more overlapping letters between words, the more likely the cockatoo answered incorrectly. Our results strongly suggest that parrots may have the ability to learn grapheme–phoneme correspondences. (shrink)

The Merge model suggests that lexical effects in phonemic processing reflect the activation of post-lexical phonemic representations that are distinct from prelexical phonemic input representations. This distinction seems to be unmotivated; the phoneme fails to capture the richness of prelexical representation. Increasing the information content of input representations minimizes the potential necessity for top-down processes. Footnotes1 The author is also affiliated with the Department of Psychology, Salem State College.

Vowel phonemes are a part of any acoustic speech signal. Vowel sounds occur in speech more frequently and with higher energy. Therefore, vowel phoneme can be used to extract different amounts of speaker discriminative information in situations where acoustic information is noise corrupted. This article presents an approach to identify a speaker using the vowel sound segmented out from words spoken by the speaker. The work uses a combined self-organizing map - and probabilistic neural network -based approach to segment the (...) vowel phoneme. The segmented vowel is later used to identify the speaker of the word by matching the patterns with a learning vector quantization -based code book. The LVQ code book is prepared by taking features of clean vowel phonemes uttered by the male and female speakers to be identified. The proposed work formulates a framework for the design of a speaker-recognition model of the Assamese language, which is spoken by ∼3 million people in the Northeast Indian state of Assam. The experimental results show that the segmentation success rates obtained using a SOM-based technique provides an increase of at least 7% compared with the discrete wavelet transform-based technique. This increase contributes to the improvement in overall performance of speaker identification by ∼3% compared with earlier related works. (shrink)

Decision theory has at its core a set of mathematical theorems that connect rational preferences to functions with certain structural properties. The components of these theorems, as well as their bearing on questions surrounding rationality, can be interpreted in a variety of ways. Philosophy’s current interest in decision theory represents a convergence of two very different lines of thought, one concerned with the question of how one ought to act, and the other concerned with the question of what action consists (...) in and what it reveals about the actor’s mental states. As a result, the theory has come to have two different uses in philosophy, which we might call the normative use and the interpretive use. It also has a related use that is largely within the domain of psychology, the descriptive use. This essay examines the historical development of decision theory and its uses; the relationship between the norm of decision theory and the notion of rationality; and the interdependence of the uses of decision theory. (shrink)

I agree with Norris et al. that feedback to a phonemic level is never necessary, but disagree strongly with their reason why this is true. I believe the available evidence indicates that there is no feedback because there is no phonemic level employed in the perceptual processing of speech.

The prime objective of this paper is to conduct phoneme categorization experiments for Indian languages. In this direction a major effort has been made to categorize Hindi phonemes using a time delay neural network (TDNN), and compare the recognition scores with other languages. A total of six neural nets aimed at the major coarse of phonetic classes in Hindi were trained. Evaluation of each net on 350 training tokens and 40 test tokens revealed a 99% recognition rate for vowel classes, (...) 87% for unvoiced stops, 82% for voiced stops, 94.7% for semi vowels, 98.1% for nasals and 96.4% for fricatives. A new feature vector normalisation technique has been proposed to improve the recognition scores. (shrink)

Casey O’Callaghan has argued that rather than hearing meanings, we hear phonemes. In this note I argue that valuable though they are in an account of speech perception – depending on how we define ‘hearing’ – phonemes either don’t explain enough or they go too far. So, they are not the right tool for his criticism of the semantic perceptual account (SPA).