.Make sure compatibility with multiple frameworks, including.NET 6.0,. NET Platform 4.6.2, and.NET Criterion 2.0 and also above.Minimize dependences to stop version disputes and also the demand for tiing redirects.Transcribing Audio Info.Some of the primary capabilities of the SDK is actually audio transcription. Programmers can easily transcribe audio reports asynchronously or in real-time. Below is an example of exactly how to transcribe an audio data:.using AssemblyAI.using AssemblyAI.Transcripts.var client = brand 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 documents, similar code could be used to achieve transcription.await utilizing var stream = new FileStream("./ nbc.mp3", FileMode.Open).var records = await client.Transcripts.TranscribeAsync(.flow,.new TranscriptOptionalParams.LanguageCode = TranscriptLanguageCode.EnUs.).transcript.EnsureStatusCompleted().Console.WriteLine( transcript.Text).Real-Time Audio Transcription.The SDK also sustains real-time sound transcription making use of Streaming Speech-to-Text. This function is especially practical for applications calling for urgent handling of audio information.making use of AssemblyAI.Realtime.await making use of var scribe = new RealtimeTranscriber( brand-new RealtimeTranscriberOptions.ApiKey="YOUR_API_KEY",.SampleRate = 16_000. ).transcriber.PartialTranscriptReceived.Subscribe( records =>Console.WriteLine($" Limited: transcript.Text "). ).transcriber.FinalTranscriptReceived.Subscribe( records =>Console.WriteLine($" Final: transcript.Text "). ).wait for transcriber.ConnectAsync().// Pseudocode for acquiring audio coming from a microphone as an example.GetAudio( async (portion) => wait for transcriber.SendAudioAsync( piece)).wait for transcriber.CloseAsync().Using LeMUR for LLM Apps.The SDK includes along with LeMUR to permit creators to create large foreign language version (LLM) functions on vocal records. Listed here is an instance:.var lemurTaskParams = brand-new LemurTaskParams.Cause="Offer a quick conclusion of the transcript.",.TranscriptIds = [transcript.Id],.FinalModel = LemurModel.AnthropicClaude3 _ 5_Sonnet..var reaction = wait for client.Lemur.TaskAsync( lemurTaskParams).Console.WriteLine( response.Response).Audio Cleverness Designs.Furthermore, the SDK comes with integrated help for audio cleverness designs, permitting sentiment analysis and also other enhanced functions.var records = wait for 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)// GOOD, 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 source: Shutterstock.