.Ensure being compatible with multiple platforms, including.NET 6.0,. Web Framework 4.6.2, and.NET Requirement 2.0 and above.Reduce dependencies to prevent version disagreements and also the requirement for tiing redirects.Transcribing Sound Record.One of the major performances of the SDK is actually audio transcription. Creators can easily translate audio files asynchronously or even in real-time. Below is an example of exactly how to record an audio report:.using AssemblyAI.using AssemblyAI.Transcripts.var customer = new AssemblyAIClient(" YOUR_API_KEY").var records = await client.Transcripts.TranscribeAsync( brand-new TranscriptParams.AudioUrl="https://storage.googleapis.com/aai-docs-samples/nbc.mp3". ).transcript.EnsureStatusCompleted().Console.WriteLine( transcript.Text).For neighborhood files, comparable code may be made use of to achieve transcription.await using var flow = new FileStream("./ nbc.mp3", FileMode.Open).var transcript = await client.Transcripts.TranscribeAsync(.flow,.brand new TranscriptOptionalParams.LanguageCode = TranscriptLanguageCode.EnUs.).transcript.EnsureStatusCompleted().Console.WriteLine( transcript.Text).Real-Time Audio Transcription.The SDK additionally supports real-time sound transcription utilizing Streaming Speech-to-Text. This attribute is actually especially helpful for requests demanding instant handling of audio data.using AssemblyAI.Realtime.await using var transcriber = brand new RealtimeTranscriber( new RealtimeTranscriberOptions.ApiKey="YOUR_API_KEY",.SampleRate = 16_000. ).transcriber.PartialTranscriptReceived.Subscribe( records =>Console.WriteLine($" Limited: transcript.Text "). ).transcriber.FinalTranscriptReceived.Subscribe( transcript =>Console.WriteLine($" Last: transcript.Text "). ).await transcriber.ConnectAsync().// Pseudocode for getting sound from a mic as an example.GetAudio( async (piece) => await transcriber.SendAudioAsync( part)).await transcriber.CloseAsync().Using LeMUR for LLM Apps.The SDK integrates along with LeMUR to enable developers to build huge language version (LLM) apps on voice records. Here is actually an instance:.var lemurTaskParams = brand-new LemurTaskParams.Motivate="Give a quick recap of the transcript.",.TranscriptIds = [transcript.Id],.FinalModel = LemurModel.AnthropicClaude3 _ 5_Sonnet..var feedback = await client.Lemur.TaskAsync( lemurTaskParams).Console.WriteLine( response.Response).Audio Intelligence Styles.Also, the SDK possesses built-in help for audio cleverness models, making it possible for view analysis as well as other advanced attributes.var records = wait for client.Transcripts.TranscribeAsync( brand-new TranscriptParams.AudioUrl="https://storage.googleapis.com/aai-docs-samples/nbc.mp3",.SentimentAnalysis = correct. ).foreach (var lead to transcript.SentimentAnalysisResults!).Console.WriteLine( result.Text).Console.WriteLine( result.Sentiment)// BENEFICIAL, NEUTRAL, or downside.Console.WriteLine( result.Confidence).Console.WriteLine($" Timestamp: result.Start - result.End ").To learn more, see the main AssemblyAI blog.Image resource: Shutterstock.