RWTH ASR Systems for LibriSpeech: Hybrid vs Attention -- w/o Data Augmentation

We present state-of-the-art automatic speech recognition (ASR) systems employing a standard hybrid DNN/HMM architecture compared to an attention-based encoder-decoder design for the LibriSpeech task. Detailed descriptions of the system development, including model design, pretraining schemes, training schedules, and optimization approaches are provided for both system architectures. Both hybrid DNN/HMM and attention-based systems employ bi-directional LSTMs for acoustic modeling/encoding. For language modeling, we employ both LSTM and Transformer based architectures. All our systems are built using RWTHs open-source toolkits RASR and RETURNN. To the best knowledge of the authors, the results obtained when training on the full LibriSpeech training set, are the best published currently, both for the hybrid DNN/HMM and the attention-based systems. Our single hybrid system even outperforms previous results obtained from combining eight single systems. Our comparison shows that on the LibriSpeech 960h task, the hybrid DNN/HMM system outperforms the attention-based system by 15% relative on the clean and 40% relative on the other test sets in terms of word error rate. Moreover, experiments on a reduced 100h-subset of the LibriSpeech training corpus even show a more pronounced margin between the hybrid DNN/HMM and attention-based architectures.Comment: Proceedings of INTERSPEECH 201

Hybrid language processing in the Spoken Language Translator

The paper presents an overview of the Spoken Language Translator (SLT) system's hybrid language-processing architecture, focussing on the way in which rule-based and statistical methods are combined to achieve robust and efficient performance within a linguistically motivated framework. In general, we argue that rules are desirable in order to encode domain-independent linguistic constraints and achieve high-quality grammatical output, while corpus-derived statistics are needed if systems are to be efficient and robust; further, that hybrid architectures are superior from the point of view of portability to architectures which only make use of one type of information. We address the topics of ``multi-engine'' strategies for robust translation; robust bottom-up parsing using pruning and grammar specialization; rational development of linguistic rule-sets using balanced domain corpora; and efficient supervised training by interactive disambiguation. All work described is fully implemented in the current version of the SLT-2 system.Comment: 4 pages, uses icassp97.sty; to appear in ICASSP-97; see http://www.cam.sri.com for related materia

Injecting continuous time execution into service-oriented computing

Service-Oriented Computing is a computing paradigm that utilizes services as fundamental elements to support rapid, low-cost development of distributed applications in heterogeneous environments. In Service-Oriented Computing, a service is defined as an independent and autonomous piece of functionality which can be described, published, discovered and used in a uniform way. SENSORIA Reference Modeling Language is developed in the IST-FET integrated project. It provides a formal abstraction for services at the business level. Hybrid systems arise in embedded control when components that perform discrete changes are coupled with components that perform continuous processes. Normally, the discrete changes can be modeled by finite-state machines and the continuous processes can be modeled by differential equations. In an abstract point of view, hybrid systems are mixtures of continuous dynamics and discrete events. Hybrid systems are studied in different research areas. In the computer science area, a hybrid system is modeled as a discrete computer program interacting with an analog environment. In this thesis, we inject continuous time execution into Service-Oriented Computing by giving a formal abstraction for hybrid systems at the business level in a Service-Oriented point of view, and develop a method for formal verifications. In order to achieve the first part of this goal, we make a hybrid extension of Service-Oriented Doubly Labeled Transition Systems, named with Service-Oriented Hybrid Doubly Labeled Transition Systems, make an extension of the SENSORIA Reference Modeling Language and interpret it over Service-Oriented Hybrid Doubly Labeled Transition Systems. To achieve the second part of this goal, we adopt Temporal Dynamic Logic formulas and a set of sequent calculus rules for verifying the formulas, and develop a method for transforming the SENSORIA Reference Modeling Language specification of a certain service module into the respective Temporal Dynamic Logic formulas that could be verified. Moreover, we provide a case study of a simplified small part of the European Train Control System which is specified and verified with the approach introduced above. We also provide an approach of implementing the case study model with the IBM Websphere Process Server, which is a comprehensive Service-Oriented Architecture integration platform and provides support for the Service Component Architecture programming model. In order to realize this approach, we also provide functions that map models specified with the SENSORIA Reference Modeling Language to Websphere Process Server applications

Hybrid computer system programming technology with adaptation and scaling of calculations

The paper considers the programming technology for hybrid computer systems, which contain reconfigurable and microprocessor computational nodes. The base of the programming technology for hybrid computer systems is the high-level programming language COLAMO with extensions, which allow descriptions of various types of parallel calculations such as structural, structural-procedural, multi-procedural and procedural forms of organization of calculations in a unified parallel-pipeline form. The suggested parallel-pipeline form allows modifications of forms of organization of calculations. Such modifications are performed automatically by the COLAMO language preprocessor, which takes into account current configuration of the hybrid computer system. Owing to the suggested technology, the program can be automatically adapted to the changed architecture or configuration of the hybrid computer system without any modifications of the source code made by the developer. Specially for this the source parallel program, developed in the programming language COLAMO, is transformed by the pre-processor into the canonical form. Then the pre-processor estimates the available computational resource, detects effective parameters of implementation of the program on the available resource and, if necessary, reduces the program performance to adapt it to the current configuration of the hybrid computer system. The technology provides two-way scaling: for increasing of the available computational resource (induction), and for reducing of the available computational resource (reduction), which provides resource independence of programming during implementation of the program, i.e. the developer is not “bound” to the available hardware resource of the computer system

Performance evaluation of a distributed integrative architecture for robotics

The eld of robotics employs a vast amount of coupled sub-systems. These need to interact cooperatively and concurrently in order to yield the desired results. Some hybrid algorithms also require intensive cooperative interactions internally. The architecture proposed lends it- self amenable to problem domains that require rigorous calculations that are usually impeded by the capacity of a single machine, and incompatibility issues between software computing elements. Implementations are abstracted away from the physical hardware for ease of de- velopment and competition in simulation leagues. Monolithic developments are complex, and the desire for decoupled architectures arises. Decoupling also lowers the threshold for using distributed and parallel resources. The ability to re-use and re-combine components on de- mand, therefore is essential, while maintaining the necessary degree of interaction. For this reason we propose to build software components on top of a Service Oriented Architecture (SOA) using Web Services. An additional bene t is platform independence regarding both the operating system and the implementation language. The robot soccer platform as well as the associated simulation leagues are the target domain for the development. Furthermore are machine vision and remote process control related portions of the architecture currently in development and testing for industrial environments. We provide numerical data based on the Python frameworks ZSI and SOAPpy undermining the suitability of this approach for the eld of robotics. Response times of signi cantly less than 50 ms even for fully interpreted, dynamic languages provides hard information showing the feasibility of Web Services based SOAs even in time critical robotic applications

Learning Fault-tolerant Speech Parsing with SCREEN

This paper describes a new approach and a system SCREEN for fault-tolerant speech parsing. SCREEEN stands for Symbolic Connectionist Robust EnterprisE for Natural language. Speech parsing describes the syntactic and semantic analysis of spontaneous spoken language. The general approach is based on incremental immediate flat analysis, learning of syntactic and semantic speech parsing, parallel integration of current hypotheses, and the consideration of various forms of speech related errors. The goal for this approach is to explore the parallel interactions between various knowledge sources for learning incremental fault-tolerant speech parsing. This approach is examined in a system SCREEN using various hybrid connectionist techniques. Hybrid connectionist techniques are examined because of their promising properties of inherent fault tolerance, learning, gradedness and parallel constraint integration. The input for SCREEN is hypotheses about recognized words of a spoken utterance potentially analyzed by a speech system, the output is hypotheses about the flat syntactic and semantic analysis of the utterance. In this paper we focus on the general approach, the overall architecture, and examples for learning flat syntactic speech parsing. Different from most other speech language architectures SCREEN emphasizes an interactive rather than an autonomous position, learning rather than encoding, flat analysis rather than in-depth analysis, and fault-tolerant processing of phonetic, syntactic and semantic knowledge.Comment: 6 pages, postscript, compressed, uuencoded to appear in Proceedings of AAAI 9

Quantitative Performance Evaluation of Uncertainty-Aware Hybrid AADL Designs Using Statistical Model Checking

International audience— Architecture Analysis and Design Language (AADL) is widely used for the architecture design and analysis of safety-critical real-time systems. Based on the Hybrid annex which supports continuous behavior modeling, Hybrid AADL enables seamless interactions between embedded control systems and continuous physical environments. Although Hybrid AADL is promising in dependability prediction through analyzable architecture development, the worst-case performance analysis of Hybrid AADL designs can easily lead to an overly pessimistic estimation. So far, Hybrid AADL cannot be used to accurately quantify and reason the overall performance of complex systems which interact with external uncertain environments intensively. To address this problem, this paper proposes a statistical model checking based framework that can perform quantitative evaluation of uncertainty-aware Hybrid AADL designs against various performance queries. Our approach extends Hybrid AADL to support the modeling of environment uncertainties. Furthermore, we propose a set of transformation rules that can automatically translate AADL designs together with designers' requirements into Networks of Priced Timed Automata (NPTA) and performance queries, respectively. Comprehensive experimental results on the Movement Authority (MA) scenario of Chinese Train Control System Level 3 (CTCS-3) demonstrate the effectiveness of our approach