A study into automatic speaker verification with aspects of deep learning

Advancements in automatic speaker verification (ASV) can be considered to be primarily limited to improvements in modelling and classification techniques, capable of capturing ever larger amounts of speech data. This thesis begins by presenting a fairly extensive review of developments in ASV, up to the current state-of-the-art with i-vectors and PLDA. A series of practical tuning experiments then follows. It is found somewhat surprisingly, that even the training of the total variability matrix required for i-vector extraction, is potentially susceptible to unwanted variabilities. The thesis then explores the use of deep learning in ASV. A literature review is first made, with two training methodologies appearing evident: indirectly using a deep neural network trained for automatic speech recognition, and directly with speaker related output classes. The review finds that interest in direct training appears to be increasing, underpinned with the intent to discover new robust 'speaker embedding' representations. Last a preliminary experiment is presented, investigating the use of a deep convolutional network for speaker identification. The small set of results show that the network successfully identifies two test speakers, out of 84 possible speakers enrolled. It is hoped that subsequent research might lead to new robust speaker representations or features

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Sketches in Voice User Interface: Relational Conversations with Virtual Personal Assistants in Domestic Spaces

Sketches in Voice User Interface explores the conversational and evocative aspects of peoples’ interactions with no-screen embodied voice user interfaces (VUIs) in domestic spaces. The project uses an annotated research through design methodology to create a series of Sketches in Voice User Interface for relational conversations with users. The research involves an autoethnographic study of existing voice-based virtual personal assistants (VPAs). Informed by these precedents Sketches in VUI are designed through iterative prototyping to explore ways in which VUIs can go beyond the existing virtual personal assistant in our everyday conversations. Unlike the conventional voice-based VPAs (Siri, Alexa, Google Assistant) operating on the commands of the user, the Sketches in VUI drive conversations and take an agentive role in human-computer conversations. Using the design research approach, this project serves as a bridge between two key contextual voices in the domain of conversational technologies. On one hand, is the tech industry’s case for usability that VUI is ‘the most natural interface.’ On the other hand, is the social sciences case critically calling VUI ‘an artificial nature’ and questioning if conversations with a machine are conversations at all. The project concludes with an ‘experience study’ to enquire into the experience of participants as they converse with the designed Sketches. The study observes how participants react to the Sketches (behavioural response) and how they feel (emotional response), comparing them to their experience of existing voice-based VPAs, captured via videography and qualitative interviews. The study findings along with the designed Sketches form an annotated portfolio of generated knowledge about relational conversations with embodied voice user interfaces in our intimate spaces