.Make certain compatibility with numerous structures, including.NET 6.0,. Internet Platform 4.6.2, and.NET Requirement 2.0 and also above.Minimize dependences to stop variation problems and also the demand for binding redirects.Translating Sound Data.One of the main performances of the SDK is audio transcription. Designers can translate audio data asynchronously or even in real-time. Below is an instance of exactly how to transcribe an audio file:.making use of AssemblyAI.utilizing AssemblyAI.Transcripts.var customer = new AssemblyAIClient(" YOUR_API_KEY").var transcript = wait for client.Transcripts.TranscribeAsync( brand-new TranscriptParams.AudioUrl="https://storage.googleapis.com/aai-docs-samples/nbc.mp3". ).transcript.EnsureStatusCompleted().Console.WriteLine( transcript.Text).For local area data, comparable code may be used to achieve transcription.await making use of var flow = new FileStream("./ nbc.mp3", FileMode.Open).var transcript = wait for client.Transcripts.TranscribeAsync(.flow,.new TranscriptOptionalParams.LanguageCode = TranscriptLanguageCode.EnUs.).transcript.EnsureStatusCompleted().Console.WriteLine( transcript.Text).Real-Time Sound Transcription.The SDK additionally holds real-time audio transcription using Streaming Speech-to-Text. This attribute is actually particularly practical for requests requiring instant processing of audio records.making use of AssemblyAI.Realtime.wait for making use of var scribe = brand new RealtimeTranscriber( new RealtimeTranscriberOptions.ApiKey="YOUR_API_KEY",.SampleRate = 16_000. ).transcriber.PartialTranscriptReceived.Subscribe( transcript =>Console.WriteLine($" Partial: transcript.Text "). ).transcriber.FinalTranscriptReceived.Subscribe( records =>Console.WriteLine($" Last: transcript.Text "). ).wait for transcriber.ConnectAsync().// Pseudocode for getting sound from a microphone for instance.GetAudio( async (piece) => await transcriber.SendAudioAsync( part)).wait for transcriber.CloseAsync().Utilizing LeMUR for LLM Applications.The SDK incorporates along with LeMUR to permit designers to build huge language model (LLM) functions on vocal data. Here is actually an example:.var lemurTaskParams = brand new LemurTaskParams.Urge="Provide a short rundown of the transcript.",.TranscriptIds = [transcript.Id],.FinalModel = LemurModel.AnthropicClaude3 _ 5_Sonnet..var response = wait for client.Lemur.TaskAsync( lemurTaskParams).Console.WriteLine( response.Response).Audio Intellect Styles.Additionally, the SDK features integrated support for audio intelligence versions, allowing view evaluation and various other state-of-the-art components.var records = wait for client.Transcripts.TranscribeAsync( brand new TranscriptParams.AudioUrl="https://storage.googleapis.com/aai-docs-samples/nbc.mp3",.SentimentAnalysis = true. ).foreach (var result in transcript.SentimentAnalysisResults!).Console.WriteLine( result.Text).Console.WriteLine( result.Sentiment)// POSITIVE, NEUTRAL, or even NEGATIVE.Console.WriteLine( result.Confidence).Console.WriteLine($" Timestamp: result.Start - result.End ").To learn more, check out the formal AssemblyAI blog.Image source: Shutterstock.