Conversational AI Guide – Types, Advantages, Challenges & Use Cases

Shaip Offering

When it comes to providing quality and reliable datasets for developing advanced human-machine interaction speech applications, Shaip has been leading the market with its successful deployments. However, with an acute shortage of chatbots and speech assistants, companies are increasingly seeking the services of Shaip – the market leader – to provide customized, accurate, and quality datasets for training and testing for AI projects.

By combining natural language processing, we can provide personalized experiences by helping develop accurate speech applications that mimic human conversations effectively. We use a slew of high-end technologies to deliver high-quality customer experiences. NLP teaches machines to interpret human languages and interact with humans.

Conversational AI Guide – Types, Advantages, Challenges & Use CasesConversational AI Guide – Types, Advantages, Challenges & Use Cases

Audio Transcription

Shaip is a leading audio transcription service provider offering a variety of speech/audio files for all types of projects. In addition, Shaip offers a 100% human-generated transcription service to convert Audio and Video files – Interviews, Seminars, Lectures, Podcasts, etc. into easily readable text.

Speech Labeling

Shaip offers extensive speech labeling services by expertly separating the sounds and speech in an audio file and labeling each file. By accurately separating similar audio sounds and annotating them,

Speaker Diarization

Sharp’s expertise extends to offering excellent speaker diarization solutions by segmenting the audio recording based on their source. Furthermore, the speaker boundaries are accurately identified and classified, such as speaker 1, speaker 2, music, background noise, vehicular sounds, silence, and more, to determine the number of speakers.

Audio Classification

Annotation begins with classifying audio files into predetermined categories. The categories depend primarily on the project’s requirements, and they typically include user intent, language, semantic segmentation, background noise, the total number of speakers, and more.

Natural Language Utterance Collection/ Wake-up Words

It is difficult to predict that the client will always choose similar words when asking a question or initiating a request. E.g., “Where is the closest Restaurant?” “Find Restaurants near me” or “Is there a restaurant nearby?”
All three utterances have the same intent but are phrased differently. Through permutation and combination, the expert conversational ai specialists at Shaip will identify all the possible combinations possible to articulate the same request. Shaip collects and annotates utterances and wake-up words, focusing on semantics, context, tone, diction, timing, stress, and dialects.

Multilingual Audio Data Services

Multilingual audio data services are another highly preferred offering from Shaip, as we have a team of data collectors collecting audio data in over 150 languages and dialects across the globe.

Intent Detection

Human interactions and communications are often more complicated than we give them credit for. And this innate complication makes it tough to train an ML model to understand human speech accurately.
Moreover, different people from the same demographic or different demographic groups can express the same intent or sentiment differently. So, the speech recognition system must be trained to recognize common intent regardless of the demographic.

Intent Classification

Similar to identifying the same intent from different people, your chatbots should also be trained to categorize customer comments into various categories – pre-determined by you. Every chatbot or virtual assistant is designed and developed with a specific purpose. Shaip can classify user intent into predefined categories as required.

Automatic Speech Recognition (ASR)

Speech Recognition” refers to converting spoken words into the text; however, voice recognition & speaker identification aims to identify both spoken content and the speaker’s identity. ASR’s accuracy is determined by different parameters, i.e., speaker volume, background noise, recording equipment, etc.

Tone Detection

Another interesting facet of human interaction is tone – we intrinsically recognize the meaning of words depending on the tone with which they are uttered. While what we say is important, how we say those words also convey meaning. For example, a simple phrase such as ‘What Joy!’ could be an exclamation of happiness and could also be intended to be sarcastic. It depends on the tone and stress.

‘What are YOU doing?’
‘WHAT are you doing?’ 

Both these sentences have the exact words, but the stress on the words is different, changing the entire meaning of the sentences. The chatbot is trained to identify happiness, sarcasm, anger, irritation, and more expressions. It is where the expertise of Sharp’s speech-language pathologists and annotators comes into play.

Audio / Speech Data Licensing

Shaip offers unmatched off-the-shelf quality speech datasets that can be customized to suit your project’s specific needs. Most of our datasets can fit into every budget, and the data is scalable to meet all future project demands. We offer 40k+ hours of off-the-shelf speech datasets in 100+ dialects in over 50 languages. We also provide a range of audio types, including spontaneous, monologue, scripted, and wake-up words.  View the entire Data Catalog.

Audio / Speech Data Collection

When there is a shortage of quality speech datasets, the resulting speech solution can be riddled with issues and lack reliability. Shaip is one of the few providers that deliver multi-lingual audio collections, audio transcription, and annotation tools and services that are fully customizable for the project.
Speech data can be viewed as a spectrum, going from natural speech on one end to unnatural speech on the other. In natural speech, you have the speaker talking in a spontaneous conversational manner. On the other hand, unnatural speech sounds restricted as the speaker is reading off a script. Finally, speakers are prompted to utter words or phrases in a controlled manner in the middle of the spectrum.

Sharp’s expertise extends to providing different types of speech datasets in over 150 languages

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