We obtain state-of-the-art classification accuracies of over 81% in distinguishing individuals with AD from those without based on short samples of their language on a picture description task. To examine the degree of heterogeneity of linguistic impairments in AD, we follow an exploratory factor analysis on these measures of speech and language with an oblique promax rotation, and provide interpretation for the resulting factors. We compute a number of linguistic variables from the transcripts, and acoustic variables from the associated audio files, and use these variables to train a machine learning classifier to distinguish between participants with AD and healthy controls. We aim to demonstrate state-of-the-art accuracy in automatically identifying Alzheimer's disease from short narrative samples elicited with a picture description task, and to uncover the salient linguistic factors with a statistical factor analysis.ĭata are derived from the DementiaBank corpus, from which 167 patients diagnosed with "possible" or "probable" AD provide 240 narrative samples, and 97 controls provide an additional 233. Relatively few studies of language in AD quantify the impairments in connected speech using computational techniques. Replace with the deployment ID for your neural voice model.Although memory impairment is the main symptom of Alzheimer's disease (AD), language impairment can be an important marker. You can also use the following endpoints. If you've created a custom neural voice font, use the endpoint that you've created. Voices in preview are available in only these three regions: East US, West Europe, and Southeast Asia.
Use this table to determine availability of neural voices by region or endpoint: Region Be sure to select the endpoint that matches your Speech resource region.
These regions are supported for text to speech through the REST API. The cognitiveservices/v1 endpoint allows you to convert text to speech by using Speech Synthesis Markup Language (SSML). This status might also indicate invalid headers. There's a network or server-side problem. You have exceeded the quota or rate of requests allowed for your resource. Make sure your resource key or token is valid and in the correct region. A common reason is a header that's too long. Or, the value passed to either a required or optional parameter is invalid. HTTP status codeĪ required parameter is missing, empty, or null.
Ispeech features code#
The HTTP status code for each response indicates success or common errors. "LocaleName": "Chinese (Mandarin, Simplified)", "Name": "Microsoft Server Speech Text to Speech Voice (zh-CN, YunxiNeural)", "Name": "Microsoft Server Speech Text to Speech Voice (ga-IE, OrlaNeural)", "ShortName": "en-US-JennyMultilingualNeural", "Name": "Microsoft Server Speech Text to Speech Voice (en-US, JennyMultilingualNeural)", "Name": "Microsoft Server Speech Text to Speech Voice (en-US, JennyNeural)", This JSON example shows partial results to illustrate the structure of a response: [ The WordsPerMinute property for each voice can be used to estimate the length of the output speech. You should receive a response with a JSON body that includes all supported locales, voices, gender, styles, and other details. header 'Ocp-Apim-Subscription-Key: YOUR_RESOURCE_KEY' Here's an example curl command: curl -location -request GET '' \ Ocp-Apim-Subscription-Key: YOUR_RESOURCE_KEY This request requires only an authorization header: GET /cognitiveservices/voices/list HTTP/1.1 For more information, see Authentication.Įither this header or Ocp-Apim-Subscription-Key is required.Ī body isn't required for GET requests to this endpoint. This table lists required and optional headers for text to speech requests: HeaderĮither this header or Authorization is required.Īn authorization token preceded by the word Bearer. Voices and styles in preview are only available in three service regions: East US, West Europe, and Southeast Asia.
0 kommentar(er)
