.Guarantee being compatible along with several structures, including.NET 6.0,. NET Platform 4.6.2, and.NET Criterion 2.0 and also above.Lessen reliances to stop model disputes and the requirement for tiing redirects.Transcribing Audio Files.One of the primary performances of the SDK is actually audio transcription. Developers may transcribe audio reports asynchronously or even in real-time. Below is actually an instance of how to transcribe an audio documents:.utilizing AssemblyAI.making use of AssemblyAI.Transcripts.var client = new AssemblyAIClient(" YOUR_API_KEY").var records = 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 documents, comparable code can be made use of to obtain transcription.wait for using var stream = brand-new FileStream("./ nbc.mp3", FileMode.Open).var records = await client.Transcripts.TranscribeAsync(.stream,.new TranscriptOptionalParams.LanguageCode = TranscriptLanguageCode.EnUs.).transcript.EnsureStatusCompleted().Console.WriteLine( transcript.Text).Real-Time Audio Transcription.The SDK additionally sustains real-time sound transcription making use of Streaming Speech-to-Text. This component is actually especially useful for uses demanding prompt handling of audio information.making use of AssemblyAI.Realtime.await utilizing var transcriber = new RealtimeTranscriber( brand new RealtimeTranscriberOptions.ApiKey="YOUR_API_KEY",.SampleRate = 16_000. ).transcriber.PartialTranscriptReceived.Subscribe( transcript =>Console.WriteLine($" Limited: transcript.Text "). ).transcriber.FinalTranscriptReceived.Subscribe( transcript =>Console.WriteLine($" Ultimate: transcript.Text "). ).await transcriber.ConnectAsync().// Pseudocode for getting sound from a microphone for example.GetAudio( async (part) => wait for transcriber.SendAudioAsync( chunk)).wait for transcriber.CloseAsync().Making Use Of LeMUR for LLM Functions.The SDK combines along with LeMUR to make it possible for developers to develop sizable language version (LLM) applications on voice records. Right here is actually an instance:.var lemurTaskParams = new LemurTaskParams.Prompt="Deliver a brief review of the transcript.",.TranscriptIds = [transcript.Id],.FinalModel = LemurModel.AnthropicClaude3 _ 5_Sonnet..var action = await client.Lemur.TaskAsync( lemurTaskParams).Console.WriteLine( response.Response).Sound Intelligence Styles.Also, the SDK includes built-in help for audio cleverness versions, enabling view study as well as various other innovative attributes.var records = await client.Transcripts.TranscribeAsync( brand 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)// BENEFICIAL, NEUTRAL, or even NEGATIVE.Console.WriteLine( result.Confidence).Console.WriteLine($" Timestamp: result.Start - result.End ").To read more, check out the formal AssemblyAI blog.Image resource: Shutterstock.