Seonghan Ryu

Phase noise optimization of CMOS VCO through harmonic tuning

An optimization technique for a low phase noise CMOS LC VCO is proposed. The combination of harmonic tuning and on-chip filtering improves both 1/f/sup 3/ and 1/f/sup 2/ phase noise more than 10 dB over a comparable reference VCO. A 2.7 V, 5.4 mA, 30% tuning range, 1 GHz voltage controlled oscillator (VCO) is designed with the technique and implemented in a 0.35 /spl mu/m CMOS process. The optimized 1 GHz CMOS differential VCO achieves -89 dBc/Hz, -116 dBc/Hz and -135 dBc/Hz at 10 kHz, 100 kHz, and 1 MHz offset frequencies from the carrier, respectively.

Unsupervised Spoken Language Understanding for a Multi-Domain Dialog System

This paper proposes an unsupervised spoken language understanding (SLU) framework for a multi-domain dialog system. Our unsupervised SLU framework applies a non-parametric Bayesian approach to dialog acts, intents and slot entities, which are the components of a semantic frame. The proposed approach reduces the human effort necessary to obtain a semantically annotated corpus for dialog system development. In this study, we analyze clustering results using various evaluation metrics for four dialog corpora. We also introduce a multi-domain dialog system that uses the unsupervised SLU framework. We argue that our unsupervised approach can help overcome the annotation acquisition bottleneck in developing dialog systems. To verify this claim, we report a dialog system evaluation, in which our method achieves competitive results in comparison with a system that uses a manually annotated corpus. In addition, we conducted several experiments to explore the effect of our approach on reducing development costs. The results show that our approach be helpful for the rapid development of a prototype system and reducing the overall development costs.

A Low Phase Noise

A low phase noise and low power LC voltage-controlled oscillator (VCO) has been designed using a 65-nm CMOS process. The phase noise is minimized by switching the differential core using a rectangular shaped voltage waveform, which is formed by a harmonic tuned LC tank assisted by a gm3 boosting circuit. The gm3 boosting circuit effectively maximizes the slope at the zero crossing point and reduces the transition time in which the switching transistor is operated at the triode region. The rectangular switching technique has improved the phase noise of the oscillator by 10 dB. The 450 mum times 540 mum chip consumes 4.34 mW. The proposed VCO has phase noises of -83.3, -110.7, and -131.8 dBc/Hz at 10 KHz, 100 KHz, and 1 MHz offset frequencies, respectively, from the 1.6-GHz carrier frequency.

LC

We developed a natural language dialog listening agent that uses a knowledge base (KB) to generate rich and relevant responses. Our system extracts an important named entity from a user utterance, then scans the KB to extract contents related to this entity. The system can generate diverse and relevant responses by assembling the related KB contents into appropriate sentences. Fifteen students tested our system; they gave it higher approval scores than they gave other systems. These results demonstrate that our system generated various responses and encouraged users to continue talking.

VCO in 65 nm CMOS Process Using Rectangular Switching Technique

This study introduces a personalization framework for dialog systems. Our system automatically collects user-related facts (i.e. triples) from user input sentences and stores the facts in one-shot memory. The system also keeps track of changes in user interests. Extracted triples and entities (i.e. NP-chunks) are stored in a personal knowledge base (PKB) and a forgetting model manages their retention (i.e. interest). System responses can be modified by applying user-related facts to the one-shot memory. A relevance score of a system response is proposed to select responses that include high-retention triples and entities, or frequently used responses. We used Movie-Dic corpus to construct a simple dialog system and train PKBs. The retention sum of responses was increased by adopting the PKB, and the number of inappropriate responses was decreased by adopting relevance score. The system gave some personalized responses, while maintaining its performance (i.e. appropriateness of responses).

Exploiting knowledge base to generate responses for natural language dialog listening agents

This paper presents a new hybrid dialog management framework that integrates a statistical ranking algorithm into an example-based dialog management approach for chat-like dialogs. The proposed model uses ranking features that consider various aspects of dialogs, including the relative importance of speech acts, dialog history sequences, and the causal relationships among speech acts and slot-filling states. The ranking algorithm enables one to aggregate these feature scores systematically and to generate diverse system responses. Additionally, the model provides detailed feedback by analyzing the causal relationships among speech acts and predicting the users possible intentions associated with a given dialog states. Simulated experimental results demonstrate that our approach is effective for task-oriented dialogs and chat-like dialogs. Additionally, a case study using elementary school students implies that the proposed system can be used for language learning purposes in addition to task-oriented services.

Acquisition and Use of Long-Term Memory for Personalized Dialog Systems

This paper discusses a domain selection method for multi-domain dialog systems to generate the most appropriate system utterance in response to a user utterance. We present a two-step approach for efficient domain selection. In our proposed approach, the domain candidates are listed in descending order of scores and then each domain is verified by content-based filtering. When we applied our method, the accuracy increased and the time cost decreased compared to baseline methods.

An Example-Based Approach to Ranking Multiple Dialog States for Flexible Dialog Management

A 2 GHz LC VCO with a large improvement in phase noise is designed and implemented in 0.13/spl mu/m CMOS process. It has phase noise of -100.7 dBc/Hz, -130.6 dBc/Hz, and -140.8 dBc/Hz at 100 kHz, 1 MHz, and 3 MHz offset frequencies from the carrier, respectively. The phase noise reduction of about 10 dB is observed for all controllable voltage range, as compared with a comparable conventional VCO. This VCO consumes 3.29 mA from a 1.8 V supply with the silicon area of 500 /spl mu/m /spl times/ 850 /spl mu/m.

A Two-Step Approach for Efficient Domain Selection in Multi-Domain Dialog Systems

We introduce a question-answering system that responds to a keywords-query by extracting information from linked data and generating reports in natural language (NL). Using entity disambiguation and distributed word similarity, we matched each keyword to a related entity and property in linked data. To extract keyword-related information, we used the entity and property to generate a SPARQL query. NL generation was performed using a NL generation template database. In our experiment, our system answered 95.1% of the user keyword questions in reasonable NL report.

A low phase noise 2 GHz VCO using 0.13 /spl mu/m CMOS process

Dialog state tracking is one of the most challenging tasks in the implementation of statistical Dialog Management (DM) systems. In development of a Korean dialog system, we implemented a generic tracking approach that can be used to extend a given initial set of system-output types. Our approach uses two methods: confidence estimation for error modeling, and dialog abstraction for dialog state tracking. We adopted a phoneme-sequence matching algorithm to estimate confidence for erroneous Korean user input. We also adopted a positive-negative model to abstract and generalize the effect of given user input and corresponding system output on dialog-state updating. Experiment result implies that our model can be used for dialog tracking without significant loss of performance. We implemented dialog system to verify that our approach is feasible in a practical Korean dialog system that can be adopted for other languages.