982 resultados para language diversity
Resumo:
Temporal variation in the abundance of fish populations and diversity of assemblages in different sections of the Neyyar River in the Western Ghats were investigated during the year 1984. A decreasing trend in the abundance of fishes from the headwaters downwards has been noted. The fish community is represented by 33 species assignable to 15 families. The diversity indices of Shannon-Wiener and Margalef and Pielou's evenness have been calculated. The diversity indices are discussed in the light of species richness in different sectors.
Resumo:
A survey was conducted in 3000 fishermen households surrounding 54 wetlands (Beels) of Assam. The fish diversity of the wetlands has been decreasing during the last few years due to some extrinsic and intrinsic factors. The total number of fish species recorded so far during the present study is 67 belonging to 21 families. Cyprinidae is the most dominant family represented by major group species (8), intermediate group species (3) and minor group species (12) of high commercial value. Among these three groups, the diversity of fish species is higher in the minor group fish. The present paper deals with the economic condition of the fishermen who mainly fish in the wetlands. The economic condition of the fishermen community is found very poor. The income of fishermen varies from Rs. 4.478 to Rs.7,484 per annum. A regression analysis shows that the income of fishermen is not dependent alone on the fish production but it is exclusively dependent on the value of the fish catch. All the three groups (in terms of value) have significant influence at 10.00% confidence level. But analysis of β shows that the intermediate fish group exhibits the highest influence on the variation of the fishermen income followed by minor and major group respectively.
Resumo:
This paper investigates a method of automatic pronunciation scoring for use in computer-assisted language learning (CALL) systems. The method utilizes a likelihood-based `Goodness of Pronunciation' (GOP) measure which is extended to include individual thresholds for each phone based on both averaged native confidence scores and on rejection statistics provided by human judges. Further improvements are obtained by incorporating models of the subject's native language and by augmenting the recognition networks to include expected pronunciation errors. The various GOP measures are assessed using a specially recorded database of non-native speakers which has been annotated to mark phone-level pronunciation errors. Since pronunciation assessment is highly subjective, a set of four performance measures has been designed, each of them measuring different aspects of how well computer-derived phone-level scores agree with human scores. These performance measures are used to cross-validate the reference annotations and to assess the basic GOP algorithm and its refinements. The experimental results suggest that a likelihood-based pronunciation scoring metric can achieve usable performance, especially after applying the various enhancements.