.Ensure being compatible with a number of frameworks, including.NET 6.0,. NET Structure 4.6.2, and.NET Requirement 2.0 as well as above.Decrease dependences to prevent version disputes and the need for binding redirects.Recording Audio Record.Some of the main performances of the SDK is audio transcription. Programmers can translate audio reports asynchronously or even in real-time. Below is an instance of how to translate an audio documents:.making use of AssemblyAI.using AssemblyAI.Transcripts.var client = brand new AssemblyAIClient(" YOUR_API_KEY").var records = wait for client.Transcripts.TranscribeAsync( new TranscriptParams.AudioUrl="https://storage.googleapis.com/aai-docs-samples/nbc.mp3". ).transcript.EnsureStatusCompleted().Console.WriteLine( transcript.Text).For nearby documents, identical code can be made use of to obtain transcription.await making use of var stream = brand-new FileStream("./ nbc.mp3", FileMode.Open).var records = await client.Transcripts.TranscribeAsync(.stream,.brand-new TranscriptOptionalParams.LanguageCode = TranscriptLanguageCode.EnUs.).transcript.EnsureStatusCompleted().Console.WriteLine( transcript.Text).Real-Time Sound Transcription.The SDK additionally sustains real-time audio transcription utilizing Streaming Speech-to-Text. This component is actually specifically helpful for applications needing instant handling of audio records.using AssemblyAI.Realtime.await using var transcriber = brand new RealtimeTranscriber( brand-new RealtimeTranscriberOptions.ApiKey="YOUR_API_KEY",.SampleRate = 16_000. ).transcriber.PartialTranscriptReceived.Subscribe( transcript =>Console.WriteLine($" Partial: transcript.Text "). ).transcriber.FinalTranscriptReceived.Subscribe( records =>Console.WriteLine($" Final: transcript.Text "). ).wait for transcriber.ConnectAsync().// Pseudocode for receiving audio from a mic for example.GetAudio( async (portion) => wait for transcriber.SendAudioAsync( part)).wait for transcriber.CloseAsync().Using LeMUR for LLM Apps.The SDK incorporates along with LeMUR to enable developers to construct large language model (LLM) functions on voice data. Here is actually an example:.var lemurTaskParams = brand-new LemurTaskParams.Trigger="Supply a brief recap of the transcript.",.TranscriptIds = [transcript.Id],.FinalModel = LemurModel.AnthropicClaude3 _ 5_Sonnet..var feedback = wait for client.Lemur.TaskAsync( lemurTaskParams).Console.WriteLine( response.Response).Sound Intellect Versions.In addition, the SDK includes built-in help for audio cleverness styles, enabling view review and various other enhanced attributes.var transcript = wait for client.Transcripts.TranscribeAsync( new TranscriptParams.AudioUrl="https://storage.googleapis.com/aai-docs-samples/nbc.mp3",.SentimentAnalysis = accurate. ).foreach (var cause transcript.SentimentAnalysisResults!).Console.WriteLine( result.Text).Console.WriteLine( result.Sentiment)// FAVORABLE, NEUTRAL, or downside.Console.WriteLine( result.Confidence).Console.WriteLine($" Timestamp: result.Start - result.End ").To learn more, visit the official AssemblyAI blog.Image source: Shutterstock.