private static async Task <AnalysedDocument> AnalyzeDocument(TextApiRequest sentimentDocument, string textAnalysisType)
{
// This example app does not yet have support for entities in v3.
string version = _useLatestVersion && textAnalysisType != "entities" ? "3.0" : "2.1";
TextApiResponse textApiResponse;
using (var client = new HttpClient())
{
var textApiUrl = Constants.TextApiBaseUrl;
if (!textApiUrl.StartsWith("http"))
{
// Make sure we support custom URL as well as from earlier versions.
textApiUrl = $"https://{textApiUrl}.cognitiveservices.azure.com";
}
client.DefaultRequestHeaders.Add("Ocp-Apim-Subscription-Key", Constants.TextApiToken);
string json = JsonConvert.SerializeObject(sentimentDocument);
var content = new StringContent(json, Encoding.UTF8, "application/json");
var response = await client.PostAsync($"{textApiUrl.TrimEnd('/')}/text/analytics/v{version}/{textAnalysisType}", content);
string responseJson = await response.Content.ReadAsStringAsync();
textApiResponse = JsonConvert.DeserializeObject <TextApiResponse>(responseJson);
}
return(textApiResponse?.documents?.FirstOrDefault());
}
private static async Task AnalyzeText(SpeechRecognitionResult speechToTextResult)
{
WriteLineInColor(speechToTextResult.Text, ConsoleColor.Cyan);
Console.WriteLine();
WriteLineInColor("Text analysis...", ConsoleColor.DarkGray);
// Prepare document for different text analysis APIs.
// All of the requests will take in exactly the same request body.
var documentRequest = new TextApiRequest
{
documents = new Document[]
{
new Document
{
language = "en",
id = "1",
text = speechToTextResult.Text
}
}
};
// Get sentiment analysis via Cognitive Services Text Analysis APIs.
AnalysedDocument sentimentResult = await AnalyzeDocument(documentRequest, "sentiment");
if (sentimentResult != null)
{
// We get back score representing sentiment.
if (_useLatestVersion)
{
// We are getting a more accurate representation of how positive, negative and neutral the text is.
Console.Write(" Sentiment is ");
WriteInColor(sentimentResult.sentiment, _sentimentToColor[sentimentResult.sentiment]);
Console.WriteLine($" with scores:");
WriteValuesInColor(" - Positive: ", $"{Math.Round(sentimentResult.confidenceScores.positive * 100, 2)}%", _sentimentToColor["positive"]);
WriteValuesInColor(" - Neutral: ", $"{Math.Round(sentimentResult.confidenceScores.neutral * 100, 2)}%", _sentimentToColor["neutral"]);
WriteValuesInColor(" - Negative: ", $"{Math.Round(sentimentResult.confidenceScores.negative * 100, 2)}%", _sentimentToColor["negative"]);
}
else
{
// We only get how potentially positive the text is in Sentiment analysis v2.
double score = sentimentResult.score;
// Try to determine if message is positive, negative or neutral.
string sentiment = score >= 0.75 ? "positive" : (score < 0.25 ? "negative" : "neutral");
Console.WriteLine($" Sentiment is {sentiment} ({Math.Round(score * 100)}%)");
}
}
else
{
WriteLineInColor(" No sentiment found", ConsoleColor.DarkYellow);
}
Console.WriteLine();
AnalysedDocument keyPhrasesResult = await AnalyzeDocument(documentRequest, "keyPhrases");
if (keyPhrasesResult?.keyPhrases?.Any() == true)
{
Console.WriteLine($" Key phrases:");
foreach (var keyPhrase in keyPhrasesResult.keyPhrases)
{
Console.WriteLine($" - {keyPhrase}");
}
}
else
{
WriteLineInColor(" No key phrases found", ConsoleColor.DarkYellow);
}
Console.WriteLine();
AnalysedDocument namedEntitiesResult = await AnalyzeDocument(documentRequest, "entities");
if (namedEntitiesResult?.entities?.Any() == true)
{
Console.WriteLine(" Entities:");
foreach (var entity in namedEntitiesResult.entities)
{
Console.WriteLine($" - {entity.name} ({entity.type})");
if (!string.IsNullOrWhiteSpace(entity.wikipediaUrl))
{
WriteLineInColor($" {entity.wikipediaUrl}", ConsoleColor.Blue);
}
}
}
else
{
WriteLineInColor(" No entities found", ConsoleColor.DarkYellow);
}
}