.Guarantee compatibility along with various platforms, including.NET 6.0,. Web Structure 4.6.2, and.NET Specification 2.0 and above.Decrease reliances to stop model problems and also the need for tiing redirects.Recording Sound Information.Among the primary functionalities of the SDK is actually audio transcription. Programmers can easily transcribe audio data asynchronously or in real-time. Below is actually an example of just how to translate an audio data:.utilizing AssemblyAI.utilizing 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 regional data, similar code could be utilized to achieve transcription.await using var flow = brand new FileStream("./ nbc.mp3", FileMode.Open).var transcript = await client.Transcripts.TranscribeAsync(.stream,.new TranscriptOptionalParams.LanguageCode = TranscriptLanguageCode.EnUs.).transcript.EnsureStatusCompleted().Console.WriteLine( transcript.Text).Real-Time Sound Transcription.The SDK additionally supports real-time audio transcription making use of Streaming Speech-to-Text. This function is especially helpful for uses demanding quick processing of audio data.utilizing AssemblyAI.Realtime.wait for utilizing var transcriber = brand 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 "). ).wait for transcriber.ConnectAsync().// Pseudocode for receiving audio from a mic for instance.GetAudio( async (piece) => wait for transcriber.SendAudioAsync( part)).await transcriber.CloseAsync().Taking Advantage Of LeMUR for LLM Apps.The SDK combines along with LeMUR to permit programmers to create big language model (LLM) apps on vocal records. Listed here is actually an example:.var lemurTaskParams = new LemurTaskParams.Prompt="Deliver a quick summary of the records.",.TranscriptIds = [transcript.Id],.FinalModel = LemurModel.AnthropicClaude3 _ 5_Sonnet..var action = await client.Lemur.TaskAsync( lemurTaskParams).Console.WriteLine( response.Response).Audio Knowledge Styles.Also, the SDK features built-in support for audio intelligence models, enabling belief evaluation and also other state-of-the-art attributes.var records = await client.Transcripts.TranscribeAsync( brand new TranscriptParams.AudioUrl="https://storage.googleapis.com/aai-docs-samples/nbc.mp3",.SentimentAnalysis = real. ).foreach (var result in 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, visit the formal AssemblyAI blog.Image resource: Shutterstock.